{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Interactive 3-D Visualization"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Importing GemPy\n",
    "import gempy as gp\n",
    "\n",
    "# Embedding matplotlib figures in the notebooks\n",
    "%matplotlib inline\n",
    "\n",
    "# Importing auxiliary libraries\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Loading an example geomodel"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Active grids: ['regular']\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "i:\\pycharmprojects\\gempy\\gempy\\core\\data_modules\\geometric_data.py:533: UserWarning: If pole_vector and orientation are passed pole_vector is used/\n",
      "  warnings.warn('If pole_vector and orientation are passed pole_vector is used/')\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Fault colors changed. If you do not like this behavior, set change_color to False.\n",
      "[1280. 1600.]\n",
      "Active grids: ['regular' 'topography']\n",
      "Setting kriging parameters to their default values.\n",
      "Compiling theano function...\n",
      "Level of Optimization:  fast_compile\n",
      "Device:  cpu\n",
      "Precision:  float64\n",
      "Number of faults:  2\n",
      "Compilation Done!\n",
      "Kriging values: \n",
      "                        values\n",
      "range                 3249.62\n",
      "$C_o$                  251429\n",
      "drift equations  [3, 3, 3, 3]\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "\n",
       "Lithology ids \n",
       "  [9. 9. 9. ... 3. 3. 3.] "
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_path = 'https://raw.githubusercontent.com/cgre-aachen/gempy_data/master/'\n",
    "\n",
    "geo_model = gp.create_data('viz_3d',\n",
    "                           [0, 2000, 0, 2000, 0, 1600],\n",
    "                           [50, 50, 50],\n",
    "                           path_o=data_path + \"data/input_data/lisa_models/foliations\" + str(7) + \".csv\",\n",
    "                           path_i=data_path + \"data/input_data/lisa_models/interfaces\" + str(7) + \".csv\"\n",
    "                           )\n",
    "\n",
    "gp.map_stack_to_surfaces(\n",
    "    geo_model,\n",
    "    {\"Fault_1\": 'Fault_1', \"Fault_2\": 'Fault_2',\n",
    "     \"Strat_Series\": ('Sandstone', 'Siltstone', 'Shale', 'Sandstone_2', 'Schist', 'Gneiss')}\n",
    ")\n",
    "\n",
    "geo_model.set_is_fault(['Fault_1', 'Fault_2'])\n",
    "geo_model.set_topography()\n",
    "\n",
    "gp.set_interpolator(geo_model)\n",
    "gp.compute_model(geo_model, compute_mesh=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Basic plotting API"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Data plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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DML4Qjf9zC2/Tg2jPT1Dbn2ezpb+AdD+AzqcOCT+Xp5beOOFrMkATCBtQV/cDyMxPAsjmVmMn4uJgMKrem70FHAAQiyoAcnlEo3//5nU8f+G2/SRsAxiGYVoLGwCGYRgvPAZ+kROQbcAGWZjK08wv77O9MXwhsWo+Hl8HgNo6hPFiY5MBmuPD2SIqnx8lzXlNxq0tUrTcfGK99BRAVGsD0NlZtgc3r58FnG3A//b/8F/8z//9n23kthmGYRiCDQDDMIwzHtJfRrYBTbMwlZe/pHiCow0QNb77ByIAHlcSkMZWL5jGhkzIh7NFwyhdOOzVVJSkv0xAB2ptQHp+0tR1eY2iKUL3C6gRUElVAYTQJj9FNgAVJ7AwlZ+aGwOHAhiGYVoEGwCGYRgrHtJfjPu10JwNsOh+CxYb4NjeZ8K4CKCQNQAoarkVaUNOwKLprz8sV+5anIBd+suQDVh4Onn6WGjfsRAdvHOvfKpoqO1k77kxzMgvCUbIEqQBZCvJRLFQ2QlQb1Ah/WXYBjAMw2wQNgAMwzBlvLf83aS/jH8b4C39ZebH17tXzf22aMDPbz0nHlMvILIBAAKRR0D9GgBvTU9OQFV9fUyk5ydf7g2e2B9EzkxHy1XCZ05GIdkAC7FwG2yjgrMFZOYnKvXBazP5D4MJFFMh+8vZBjAMwzQNGwCGYZgWSH8ZbxvgX/p3S1v+lOpDNkCW/jKhmKqFFoUN8OD9R4XC3nMxn/fhDs0/frk3iN6gONiVK982OQGyAQLLkGDZBmTmJwCoAeQKoKei4TYASKwBbAMYhmFaBhsAhmF2Nd/89X+ROOLVNFMLLizOjHY33ljT0iwIzUp/IjkyAgAjABA9oQJI9A0CSKfTALq6urTQIq0MxdQXu865nfn9R/Vb9/ihKv3dKTuBE6ccnyUnQDagsDQrP0UBgVxeyeXXAAgbcPXnN179nLVVKHhuAMMwTIOwAWAYZreTejAKwG4DMnMTANTQIiqTtpqwAQDmRq0zwtzoORGmRP9yh58KyZGRoeHh+x33AKSXlh6PLnV17UnNjAEIdEcAaKFy0e0Okf5E54F+APAcItathEB1AELoA6T7w53X6EMql19bnC50dLbXvSJ3CmIYhvEDGwCGYRig1gaQ9LfTqA1Iu7TCtHN6XwgAnDr8AOh6K07qH0DXnj2PgXR6KbFPB5CaSUe7v7qna81N+vvX/S/1BoGgKAK2Q4n+qCf9y7rfcjBr/trf/gqAjDjbXPWbc/LgIIB7c2MAgrG7wRgArGZLQGBxuhCMqPGOdtOhBLqK/+gKwzAMwwaAYRimSurBqBasM8zLpw24Obp4pKf+FcvS34n9A5GP0rfzWQNLNccT+/R0Op1OI77/a9HuEtYNR/XfoPQvQ81/LDZgI9LfytQEKuUBFgb66fyD92bHAJgldXmuFO+os/HP0p9hGKZR2AAwDMM0gx8b8GBhD4AjPUuOz3pI/4/S1UlY4ZgaKtQ00Q9E73dEf6W4rJZWnSV+c9JfhmzAX3/wiaIGWiX95dFgVB4gbECw7a688mTvIAD0AgCZATdu3/sEwF7ldN2rMwzDMAI2AAzD7Gq+9//5v37z1/9F0y8nGwBPJ/AwFUbqeQDHD98E0HOiEmFw6usvS3/Bnq49S+klALn0/wZAJBANAUggnU5bWv77l/6hp7deOvcFt2dJrHsPBSMalf4yXTkzGLubdikPIMpmwNMJPDXL/oGdAMMwjB/YADAMs6vxM+63u++8EPpuOAYEVDUrf/lw8UUAPSccJD5cpL8gv/xrAFQVkLr+d3V1AdBCi3V1/3LBNPVSZzR48VA57JB0LnNwFet2NiL9AQRjZdXela20Da3nBKreyYWn5l2uA2YYhqkLGwCGYXYpQvpT4S8VAVvoPHhKC+5BRdk3ZAMC4Vmj2EXHg9FqDs9H758F8OLFqtynvv5aqBdAtOcdyznnH/ySeNweqPbup67/i0sHkT/U4ZpMhOVCWV7Hw6ph6Fdncq/2ue7rX51KAYmBWMr7n9kq6W+BnICjDagr/QEsTueDEfXs5+qvZBiG2eUopndjBYZhmM8cHrv+ogi482C5e719ClhdG0A8XjdJ9wsbYCGoQ1E18aVo5A8g2vOOm+4Xi1OZXgClUgnAnkiHZYHQ/QA6QgoAw9DlBZ9Ojpmm/svDl+SDV6eq0t9uA3zV+LpLf4vunw5PHM87jwiAZAO8pT/VAJD0pyNiUADPBGAYhnGDDQDDMLsFP9k+dtzGAPuxAZMzY/J4AYsTcDMApOwBaMEli/SnNWJBPBBbSqcB7OmqOTOA+/c+SfSdJ+lfvnrFADxJrwDIzE18+ctvJ0eSAIQNkA0AQTagtVv+3SfCAD54VP4GutkAWuY2QID4+U8+ENKfsEwKYxvAMAxjhw0AwzCffZqT/oSbASA2YgPsBkAoewDxivRXg0vymsnRFICjx2t27i1cPBT64ZUP6XF3X7mINm9gKZ3OzE3s2bMHwNLS0pe/XJ5VTDZgaHhoYuqhOAkJ+q+84XUheaUjjtKfEAaAkG1At23X324D5O6fcn2wbABoDZcEMAzDWOAaAIZhPstsRPr7wU9tQH/fIEzz3tOuPfsyAMLKEgCjtEcsKEv/XHVfX365USyvJCfQHmgDsDgzBkncC0SNr2BxZqwIrbtvMDN/RwVI/VsYGh6iB0VTA5B9fAdAIFS/BZBP6U+CPvnwvSG87raeMoLs0p/olMYJ2xv/U6cg2QbwcACGYRgP2AAwDPOZhfp7yrvvMjTuVy/mPdb4RDT/sTuB2eVD9CAaxqtdhwDcWBgDoAaWAKTXDgEg6R+3JfoLKM8n9PQ2gPR6NWybTr8LINE3uKeryy79ARShVW5sTNXqv+GToA+EafaWXnelI3bpL0g+vDx0+A3L+sWpPBVLdL/ile6/KDS9S1IQ2QCW/gzDMHVhA8AwzGccau8jS3yS/t5rmkMOCAjpDyCoV1X7yz2DAP76fhoAFMBT+oM29Q/tSyaTQ0NDAERuDwB0HgXwlbMJ+6uE9D/VW64P1oIRAHcfenX46TzQnyuUABhrj8UZLFydSrm1CfKQ/kSgNl+fpL/cIsmRxVpN79Y2lMqFqSwYPBOAYRjGHTYADMPsCkjiU4cf7zUtsQGXR24U86OJvvOy9CeoZ3886CX6CXlTf2hoSHgAoCz9O8IOe+FPQfv3Vekvc/pwAp42IBoKAMhhPwBj7XEKMQAJ1Aw0GM8mILUJ8kj0FyQfvheIVO92cSq/nCo2Kv0tiLahjp2CaDoY2wCGYRg7bAAYhmFqaIkNCOgIBNpyc9Mr+bVEJVPf/5hex3weAMlkEvuf99D9E48yQMYw9PbuPiDjdv7ThxMfrmbdnoVkAyYepk8d7iIbgFonMJ5NqGoOwGDFy7hl8Mv80c+SQ4deB/BC4hyAj1O3HJd5S39B94lwN4Cs6dYsiEeDMQzD2GEDwDAM40DTNiCxWrPlHwi3LedN09SD4bZOHy93k/7vPyq0nXoDQBsAoJhfE09J0r9KMNK2gLbi+hqAg+Gap7oO9gPA+EPUoyMeBzDxMA3g1OEuACnEimYmqOgk/QGk5yfenY99/Ze8CgaIxSkH/0M2AJIT8C/95S87sw4d7ZbnigB4NBjDMIwFNgAMwzCupB6MqqEFUePrjUX6A+VEHQQiCtAZ8Xq/ddP9cIkbBMNtANby67BJ/5plkTYAc+sAcDiYL0t/HwTD1hZAwgYEIrN6sUuHujZ/R8rg9zIAf/SzJIBA2Cvh54XEuQ8ejXqMBhN4xxkCBgCkHhflg9/67jfoAY8FYBiGARsAhmE+q/zm7/wx7d/TXr4jNO7XYwFBRb0eNsBD+gMIeCa6Nyr9CarQDYW9WoISol1P16n6Hf3hJP1lJh6m5z9djkYmAxEFkT3Fyr87ZQYTSrbyuFresDht3c53tAGk6acfYTo8gXqjwbyhXX/6bCvZLkVOgG0AwzC7HDYADMN81rD0/ne0AST95QX2NRbsNsBB9wvVvsnSX3DqUOfiDN1euQu+cAIenTrdOHfyICqb/XbS85MAouG41n4IpY9oLoEYUyDrfjhJf0Hy0XtUBgAXTW+xAX50v0gckksLKBogw01CGYZhwAaAYZjPDN4zv/xk89eNGKBiA07tsW63k2RfLpQtQTCgmYZrVoxHor/bS+xNOU8dcq4pWJwZ0zp6zbUnbqeqC6X7yzYgXeslIoE4Ap9fL60opY/U4FIwdhe2CV+L4VEA3fnzNx+9Y7+EH00/HZ5Ynit+8ZWXvJc51gzIpQVUHrA4lU+7FAozDMPsNtgAMAzzzNPacb+yDVBDC5Znu1dNAKnVUQCJvvOwSX+BopYlu3ACHlv+qDT4t2fy2Lf8PU4S6OyLhjWYJsKHsvliS2zA8sqK44JYWEP4Qq64WiydAazfKGIxPHroxH7ZBnSfCJ3r/mLKBACRNWR9VWU0mDd+yoVfSJwTy0Tb0LqvYhiG+WzDBoBhmGeY1kp/GbIB6fmkONJtS/hJzYwCmL6XU1Q14V4hoKhaR0jxVv8COaG/GekvEQsHW2IDbt3LibEAdFDVqsI9GmwPRtTRsQ4A5wenHE+yGB6NoCvcs6YXzHPdXxTHKWtItgHNjQZriIvT9RsWMQzDfLZhA8AwzDNJXemfmZuQE/2bQ0z2tat/AOPFQwB03AtUzIDdBnSEFNTb+7czPzMOKRrQqPSXETbAz3Wp67/9OI0FQOhQrlAy1h6rwbRR7AIQrJ3sOzp2AjYbsDiVD0QUeQqYBbIB5vSSfTSYPf9nI9L/1GNbTQDDMMyuhA0AwzDPJB59+jNzE3XXNMSpPYPYU5b4qOj+rOmQxS7bgCakv2XLf3Fm7FRvR3e9+y9lZlaAojRxzEIgFO0IRe/MpACc6Us4rpmcXaUHctd/O4XUfQBALBxfBkA2wALZgNCe63WlP1EpF471JV4BkEDWcTqY//kAlnairPsZhmEssAFgGOYZxiLxhfT3WNM0ib7z7z8qFPNrjtKfiPUc1xT4T/gRPEW7NeGnt4MeLD4YBVDXBgTDbStP7ltsQCBk7elJNkAgdL8Fuw3IzE8GwtFAOArg9KEL04sfAlCDabjYgNT8l82ACvxnj3t27BSUQqwv8YpsA/xIf0tVMfUR+sqDk5Zll+JBANf+d38XwKV//yd1T8swDPOZhA0AwzDPPKkHo1qwTleZDdqAaqWvElMUWDr8xHqOA9AUAOgIN6b+aY6vQOh+Cw3ZgPjeo3bpbyHac8RN/QsmHqbT85OlfE5If8Hx7pcAeNgAVdEQ0nV8zSioAIIBBycgOgXZnyIb8MGjj+uOBnNsKBQrAMDPD9wD8Ln5k6hIfxm2AQzD7FrYADAMs4towgaMTxaCumlp8kMdfsgGxPceF9K/oZuxSP/XXntj0bMD6XwpMT81O3ii121BoLMPQDSs0RrLZn+jiNafocQxUf5rwW4DIDkBVdEAqGEYpl4s/G0N/9HxJI42oPt4GMDirDYRngpAd7QBbr1EY1Iz1YWp/F8Hbv8fu593XAm2AQzD7ErYADAMs+vwbwN+8Cd/s7//kpuuJxuw8nQ6rqy75d87YpH+Atrgt9uA+ZJz4r5ASH/5IKX7N2EDLF3/o6GAKP91XC/bAAgnUKjezMrjaQDtR1S94NqBR9gAkv4yJWgT4SkAwgl4jBF4NPYJVUzfmy90BJSOgJcru7ZSro32NSSZYRjmswIbAIZhdineNkALLgDo7Gp/PHkNwIF+B4lIZb7FiAa0LT+5X3IvwyXcdL8F2QbUlf4Aivm1uHsXILIB196/1nmgv+6p0u7Dg4UNcFtgtQGBNIClhwsAlEprn+69PVOpGwBOJF62vDwzWwBw+hWvVK4StA8Wx7968QXvf8XiVD6uKX0A8mamzdkACOnPMAyzC2EDwDDMMwY1APWe2is3APWe7Gu3AST9ZRQTjyeuAdh/qmwD5A4/P5wpLwuE25af3AeAE3ssZ/Ap/WW6j5y/cuVyMT9XN7bgWP4rSM9NAjh9OKEXZ+8+TMGpV2lmfhJA/8H2vYe6ANx9lHa7ViF1PxCOAn1uC4QNyGX2FvPvaSEAMEpdlmVkA8pXn3Wdf1xzk5Vl9ukBgsWpfCR6Oq5Vf+Kda+apxwa6q2tY+jMMw7ABYBjm2cCx8b/FBjg2/ve2CgQ9u/fkAcvxgA6lkvzf0TuQW1vev6cTUnPPZDKZXq+WB4SejA0ND8nNQJuQ/jLe4t5jJel+C6cPJwDAnL37MKXEDwPIzE/2H2zfe7DmJk872QC5C1Bdjne/tLRwNxz9nGHqxfX3KBpgwWdbT+olaj9usQHy2ToGyg5n/09vyi9h6c8wDEOwAWAYZnv4zd/5Y1MvAvjOt79Zd6X3Aj/Z/HVtwHyufX5s6bnB8uZ9Qpr81dE7QA80tSz9k8mkeLarqwvApUNBAMknSI6Unzo31A4ffXv80KgNSEcddsdlTh9OJJN/eebtL1ukf82aig1oSPoLIoE4gPXSSjj6OVNZLRn/ASin9wix3tkbyhVXABSeOmT+LE7nu3E+E7lhf0qQMmOL0/kErP/ecu//gfMAlsdHt0v6v/x3f0fVAh/84f9pW67OMAzjBhsAhmG2FLua/41vfw8uNqCu9G8URxswn6sRwbL0R+fRjnYdgCYNqE0mk0NDQ+JLMSAMwNDwEIAnZrtYtvhgdL6U8Gjd45/ovoG6a9y6iDZH58H+iwdx/fYMALcKYG9i5eKEztX835v7eCqx965lQTQYB4C9NTZAng9wovtlAFOLDjZALEshRg8SyNrHfomAgBv2DqEb59Kv/j/DbYnOA2cUNTD8W3+oF3J/8+9+reVXYRiGaQ42AAzDbBHeal62AS3X/RaEDbBIfwv/6W+uA2jvOWI5Lqt/AIm+8+QBSPfLy/yU8Poh0NkXdS/zJVou/cXjaCgAwLsRkJ1AZFb0A83MT+bMtKIgtDfvuNlPNiDa6zwaDDYb4Ljs1LwBRFIu5QGOCOnf2magL/2d34l1HlS1oKIFVTVgGroSbvvcf/W7P//d/6ol52cYhtkgbAAYhtl0/Ah66j+z2dJfMHH/KbA/GEYxv2Z5KtWu3LtT1ZerCw9Mw4jvO0ZfXp5aesNW46v3vQYAlcBCC3U/pOae6XQawMhIzSb68PDQ5kl/C3UbAVlQg+nM/KSqJQIRFTkAiAbj0V7kiit2G1Cu8e11HQ0G4ET3y4vhUbv6PzVfs+vvUSUscNz1JxuAjTmBIy/93Z5jFw2jpBcLiqqZqmEaBkwDUF78+rc/+vNvN31mhmGYVsEGgGGYzcKnmifpP/HpAoBLhzb3libuP7UcCYbbgKoNGJ8sALBoQ0VVLTZAINf4Urr/lSuX4/taYwBKmZlifi3aN0jSn4oNBl8+JxaMjCRHRpLDw0Nwmh4g6JI0vdsyD90vQ/UAHl2ABGvpewACEQVYAkAGgBA2oKgUlu8F7TW+nqPBys/SAov0J1m/PPYBgPEjL8DJBvhJ+NlIQEALRPRirpTPmqYJQNECplEyDV0vrJuGNT2JYRhmW2ADwDBM6/Ej/TNzE4ZRQkX6bzZ26S9DNmAtl/XQhoqqKssPl5eBE3uSySQl/AwPDwEYqRT+AohGQytP7gOwu4UmoKLe1PzDE89/zv6suPrw8JDjELEum6y3L2tI+vspBc7MTaLS6V+0+1QD6VD7XWC/WBaPd6ytp2N9JtyKgN1HgwGIFsys8snHB/HC3CCcZP3Ag49RsQEAEkq20Vz/5mxAqbheKqyrgZxpAiYUNWAaummUSsVccX21oVMxDMNsEmwAGIZpJT6lPz1Q1a17C1qcGQXQbWuBL5NfvJNfdGiTDyAeUqnPzxOz/Tu/9/8F8Cv/4B+jIv2Hh4fEyh/+8C9pq76VNiDS7rMLkM+mQ91Hzif6FjZJ+ssIGxBsq2YuiS1/VdHUEAxTj/TmjKJqtwGBiJKJjGVSNYPDogVTXvN+4cN/1O06yZdsQMfgK0AnbM2C/NCoDSiur+bXlkxTCYTyeqmgqJpp6KahlwrZ9dXFJm6AYRim5bABYBimBfjM9hHSX+bM8QMA7kzPt/ienHCzAaeO7QVw9SEApGZGA3r5eDykotLiU67xpfY+AIaHh+Ttfzsr5dFgLegCFAy3HQikFh+kZJVvuTq1/9eL6/A0A+m5ycz8ROpBAkDiiKupIEF/7sRBj9FgxK17c4di1moKwYnEyx89vKxqimNHf1XRACCoR3pzRaUQNNvty0Qk4WDaAJCOKQAKn9afINYRUADgzvUA9GUfHYHc8F8eMD/+48PP/7JeKmrBaCAUU1XNMHTTKBXXV9eWHjV3dYZhmNbCBoBhmA3R0Ja/B2QDtgZhA0j3O9N59FhH+8VDodTMqKW9D0GVvt32J2qhCl1yC03PBOjq6np09waAR+Vt9CSkgb7Dw0NwmvzleFH7stSDMdhsgGUv33E0mIVH2TYAbjbgF37hb9+Y/rHHy1VFW5wumEph7wkEEHdbNh/PLk7nT621AYhVnIAjZelfy/L4KDZgA+AvIGCaRim/VsytQFEUNWAaRZgwjdLjOz9p+roMwzAthA0AwzBN0irpL3Cc49tyAh2HAMQiITf1H2g/CqAjrFw8FHqKdvS91l2bND/wuV8eX0h3dZW/HB4eEk+J/XjHzjxN2ABxnlO9Q44Luo+cdxz6a7+o9zJhA+xpPAL/NgCSE6BEo9xi/9mOL0UT79BBsaNfvsnpgqJCUaFAA7BeXAEQCVptwOJUHggleg1Ufq26suapx4bFhzlKf5nl8dGNeADUswGPPvnT3sG/raiaaZjQS4AJ05wd+88buSLDMEwLUahNAcMwjE82ku3jyNbo/is/GxHSn46cO3PMsuaDj+/EompQNwEUoAGwDPAam5oVj9PpdFdXl7yA1P/zJ3v83I9PG+DR20egBSOWI5QC5L0smRz53Buv2tY4lNtacKwcuHVvznJkbenRxVdecTxDtLtsA8bmfkrSX+bQ6W5UPAAqNkAMDwbQ2RsCgOxytIAXrgUAXHrldYfL3LkufxVAOa+LpgK/ffElx3trjlYNEGAYhtkaOALAMIxfnlHpj4r6F9LfzsT9p1CKQv27Idf1dokQQIXh4SHxuK5w9xkNcOztI5NMJrVgeGho2Ps8LcFn0XDdTPfc4pcAZJf/8gBey4ZurJcceuOI7f9HdxcjAWsKVrRgIhBHAB9fWgFwybG75pkLQI0NIOm/GbR2jhjDMMxmwwaAYZj6bEu2D51QL+YTzabOy5SWHy0vo2PfcfmgpTdoMNwW1M1ifo22/93w096nrnAnxAJvJ+DzbD5JJkfowUjlwXA9/9Aq6U9QllGwDZBG/NptAO36RwLtnb0heXZYTRegWLzwacGrFOPMBQDXPngPAKAGsImd+NkG+OH0W79192/+39t9Fwyz22EDwDCMF62V/j63/C0nTD0YBdASG7D8ZBpAx77jBV1zmwwQDLcBWsE2IdiCaO8jRnHZEbK+JQEBRxswNDRkye2h3v+OVyTpT+GCD8cffmHo85T6T07A0QZshvS3Y7EBcsIPIY8Q7sqWDcCTp/V39Mu7/mdeAYA7H5SgAmAbsL2c/sJv3P3pd7b7LhhmV8M1AAzDOLAt2T6OZ9OLNVqwaRtw5Wcj4vFyJh0Mtx0+VZsFrhQBUApQERqAU4c6rSe5clk8TqfTa0+mAAwNDbUwoR/+ygPkUwkDYB/75bFsZCT5haHP0xGyAaitAfA7JaBW08slwvYaACoVoPpgeTKAoPt4+ONPk5BGg+UKqweO1UxWTk0uUhcgIh1THOcAuCb83PkAwKVXXrcPCd4M2AlYOP3Wb4XaEqM/+G+3+0YYZlfDEQCGYWrYxmwfP2wwGkB1wIHsejQS9BgNZpf+MrL0pyOtSuh3O5vHqIHUzKgWDP+dv/frfq5odwgE9QAVNsCP9Hfby/ffKehYW81BMe43Stn/e1dgmxCcmS0AKASUxVOF7olyRcfFad2SAlQn1/9M2ZakzBiAzbYBHBCQOf3Wb233LTAMA7ABYBhGsMOlv0wTNkBuARQ7dpZygWAbDXbxUAiAc24QAOrL2duRfDIFIJlMCg+AVtuAsalZ0WJoeHjIPdHI8aD1ium5STf1L/CYCCbj0SdUQDbADVXLAniQOgPgSOKOkP4yZAOivQjkVVSkf5VYx+ILiKaXAeBx9YPMT5nvpXhQ/pJsADbZCbANEITaEvUXMQyzyXAKEMPsdrart4/PE1pSgOz4sQET958Wa3P6hQEgTh/dq4YWuvvOJ1ZNAE/hMPmLkIV7MpmkB7INIDaSFEQjxmBrQupRbOCBaP8veoPSvckpQD7xI/0JtxjC+P171bPNTwYi6ue+pFrW3J2tad9Z0lZ1XTeKqpwUdLx3T3VFdqUj3nH84bm6d2WR/o5sQV7QrrUBe0+8vufwS2QACtkFLgNgmG2EIwAMs3vZ+Vv+dMKUy2b5fK4dgJ/tRLHNX7SV9p4+urdm2aqZcEoKEsj793bdXz1VU9EAIf3d8O8BPMZ+NdFNyKf0r5s7pAbTAFaepgAEIlbpbyEQUQAEEM8ZK2oIam+ObECoVLNv1RHvKK2tTOy5mo20vzDnHMTwI/2JLcgLomgAdp8T2HO4lbMXGIbZCGwAGGY3ssOlv+VstMcv2wCS/o1isQGy9JdJzYwumu0t6cvp3wZcuXLZu68ogJcGDjtO+LLgPfFXkJoZTT1I1E37aZX0J9bS9wCoQQAwinvclpH0t6AqGtkAfV2lRkBGvMZCrGtr7x691l5ok22Af+kvw+UBDMN8tmEDwDC7iJZn+2CTpb8M2YBbd+77PJUbizOjgY5DFvWvhhYAdK+Wt5bnSwmPzvKC7iPnR0aSqZmyDXALCPi0AR7jBWRN73E2n9Jfhgp/HW1Aa6U/EY58fr20opQ+AqAGlwDA1sP/dO+FqdQNtzOoiqaEMRNdieiarmFfqR1Aqq1qGFZDZRvw66sv+r8xR7g8oIVw+S/D7CjYADDMrmB7h/g+TGsADnfpGz+haOQvjty6c//cmWM+70TMA04cOQ0gPZ+0LBgvHvJzHrktD6UMpWZGPUoC0KwNcNP0lrM1If1lLDZgM6S/IBKII/D59dIKgFDoD4DX7WtOJF4G4GgDFBWKqgFYh24qeBRaBRCsrRAOKFgPr/2P4Xf3ldq/mXnB8Tb+U+ImAEM33RbIawB8M/PCTrAB//zffQOAoQPAv/yHf7B597PZhGI9230LDLOr4SJghvmMsy3ZPhbGbk+Jx3Yb0NAJ5Xb+wgbUNQAffHwXlRZAxHPnq0lEizOjs8uHUBkCAKAAzVKAa8EtF3/xQdkGeJQHwMkGyBMGBANH91mOOKYAWQaBuWF5bTKZ/MIX3rKdyqEhj53mpD8qcwAI6gUUjKjnB6fcX4Gp1I1cfgWA4lQyYJj062QqphIqaY6bWhQlEEKfZH355Xr1E1B2Ah5rtmt6AEn/yi1Vjz8rNkBEAEQXIB4FwDDbCEcAGOaZgaS8qRe/8+1v+lxcl82W/nZENGDjZ1t+Mi129N2gcb81axRrp8juvvN3Rm7EpaiCnfTcJAnourUBv/IPzv/R7/1r7zuvGw041dvhfYaGkBuANlEBLNPQdDDq4ORRZrCWngKAQa9q4BOJl6dSN9aLK47PqooGwDBLpmLmgyXVVCg1SOZJYBXA9zo/fhJYPWDG3S70vc6PAaiaQ/mBZc0W2ABLQEBW/xa+9d1v4NmxAQzD7BA4AsAwzwCymjf1sn51swHbm+3jiBwBABAIR+nBmRMHGz2ViACIvv5u2/8k/WWKhbR4/NxgTQXq5ZEbAAI6OvYdA1CAhkoXTnsbTQA37y0MDw85Xpeyg+hZP2pb2AAKAsjS376131AEwKPxP0UqGooANDEYWG7hSjZARADWlh7RAzWwZO8E6oiHDQAAQzeU8seZow2QIRuQWDUXotanLAbAcQ2xNdGAf7/nbsdAjYNKrJoLUWeXsvNtwOHnfzkYaZ++9nvbfSMMs9thA8AwOxq7mhcGgJBtwE7I9nFEGAAh/WUasgFXfjYij/SCU/6PXfrLu/7UAsjNABCRfScBHIpa5Z3Q35Tnk+g7Pzw8JJ4VhQHyQfi2AfZlTRuAujO/AIyMJJ87Ye066mgAmpD+hH2Gw3wxIaS/4OIrr0S73/FzCVQKA1ydgD8bENQB4NhaeRZxJlbV08IAJCoV4cXKp6S8TECJQ5vhBP79nrvylx0Dg9ItweOW0IgTEHFFuO8ptBA2AAyzQ2ADwDA7EQ8pLxuA9PwkgN//zm/vWOlPjN2ecpT+Mt42YOL+U8MoqWrA3shfNgBW6W/L9hEM9NckDlkMQBGaPf8eTmn0qBQBE8PDQ25X9LAB1P5/8ESvZY2s7D3SeNyWeSMGgVEFcOVUNQagaelP2A2AFgzffZS2HLz4yiv0wL8NgHdAwNABkBNQTQVAEGUfEJSy5w0AwImKDQCQiSmqpgidTRRrPyXdNHcLAwIW6Q+ge616D5HT1pSq5myAY1yR2DwncPzSPwDABoBhth02AAyzs6gr5emjmqT/xKcLAC69UWee6zZKf5k7U3N119htwMT9p9n1AgCjUvnYHovKNuDcmWPeW/4yFt0vkA3ApUPBJ2a7Y16NRxv+Jkb/WsZ+ibJjsYbuwU3T+1zmhmUSMNkAYQA2KP0JRwMgHgsnIAwA0TIbgGpAgGxATAoHGLH44lQewMXaQQFBpSqmi6cvlB/d+cBy4s2zAf/d44/pwf6BKGqlP5zUf91bstuAunFFouU2gLb/C9nFR6Pfb+2ZGYZpFDYADLNT8LmLbxglVKQ/4WEAtjLR3yf+bYCQ/oRh1LQPIhtQ0LW2WK1Sb1D6E5dHbpzpD4k5AE0YAMKnDRibmrUftPQdWnww6udsPpfZsRgAIjM32RLpT3gbAOLuo7TFABCbYQNAeUHhLpL+xMVXXgeqEp8MQFX6y2yJDRAGILFmAjgwUA6deUh/P7ck24Bv/vq/QGWwBuFoAIgW2gDO/2GYnQMbAIbZZpqo2b0zPS8/ZTcA27Xln3owmvAnRj1sQK6gA1Bg1TEWA5CZn9zTewZyhx8n6Z+aGX1j+GU/t4Tbn4iHjgag62C/2HQXLf8dsdQG2KF6X8vML9kApMtddOr0HRLLmvAAjgbADw1NCZDzi9B4ilGrbQBMA4vT+bZwlzhcNgDEnQ9wxsGN1NCIDUDj5QH/3eOPE7W7/tHTg/sH6mTQ2fFwAmQAiMSR8x7qX+BtA7713W/4qTpgA8AwOwc2AAyzbWywXY+wAbIB2C7pT9cVO77N2QCS/oSHAcjMlwVoJKgA6O47b5f+tOZMf0js2Xf3ud6SnPOdmhl9YrbDM7GebEDdfv8eolzu+i9sgKXpEGoDDpazOS5ryAY0YQCaHhAmbECjKUZEq2zA4nTBMHQTZvexsFFUC0/DsBiAhvDnBBq1AT+4duPTnnJbpGjtrr+HDaCYRqlgWJY53tJP/7Ny8mD1zIZR6u7zFV6AzQnIg8kIDyfABoBhdg5sABhmG2hhze6d6XkyANsr/QWNegAAd6bmZOlPOBoAIf1jkSAA08iJZ0UlrpD+lfupSdqx2ABLuedTlKeDLT4YrZtYT500vQd+wUWU28d+xfcd82g6JJ/NPvTXcZn3XQF49+qfvvXWUHHdtS9+MLICoLge96n7UU/Wpx6MacFw00PE0IgTsNiAxelyLhnZyJ7jUQCGqRtF9YWjQ03fD9D6vKAfXCvPP37yxnOOCyw2QKQzkfoXTJuXDEN/Y/CW/ZZ++p/LX5INoKxCoq4TSM9P/v53fhvug8kIRxvABoBhdg5sABhm69ik4Vxjt6fs43XdFvs/szduN2lJ+65rA0T97tq6NV9ceADS9Iahk+4Hytk+pl6yvOTcWYf5WQ76uO88atW/kP6N4nOulkWR2w2An6ZDcGn571aZ4GYDgrE0gORI8q23huiIxQaQ9BfcvJ3pjdQpftiIrG+URnuGZpaXVufL4lg2AISiIhKMn0j4yxNzo3U24AfXbljS/R/0OM9JCIRqjgsDcGetnMVkGqVgTAMg2wCh/gWGXjrZW3NFRxuQrtjv3//Ob//aP/v6gYHqr6LdABAWG8AGgGF2DmwAGGYr2NS5vKLLvocN8Cn95UweN+3ufZP2uk/HUzn07QFQawMUKCT9o5HQ6aM9dPDO/RmxQDYAtOXfkD4+taescppW/4JGbYAwAGLsl887b6I0WbYBJP0J2QAQxfW4RfoTN29n6IFpaIdiNW1Yt1L3W/BvA+7OXs8VVwxTX503ZAOg1OrqHWUDRtLWvyO7DZANwKnHxppuPOhRhfoHYFa29mUb8P0fqZbZCEbl78jNBpD0n5obA/D5v1UC8N5Pr9NisgFuBkBAToANAMPsHNgAMMzmsqnSn5Dn7No9gB/p75bGg1rt7ucmHQ2AfCo36S+ztp7PzE8qUGTpr4YWxYLbd7OoGIAzUnufxjbIV00Aib7zGzcAhH8bcOXKZXniLzbTABAHBg5bjtgNgBvCABBkA7ZR+sv4sQF3Z6/Tg1xxxTBKy3OlvSddk+kjwTiADTmB1lUJe9sAYQBOPTYA/FCpdi5aDyqQDIAgGNNUVVucGQMgbIAhGemAgaOHqzbg8Xpnb3ydpD8hDAB9STZg3ynnWdQWvvdvSmwAGGaHwAaAYTaFzdD9cFHzsgEAkJmfHBw43tCWvwU/3Rvd8DAAAOZz7cFwm8cCAOn5SSH6CVn6115rYxkyUtPPphtujowkh4eHLMv81AZYcJvm6zHzy2OZTChWle+JI1Vt17QBCIajAExDO3W4y8/LtwBvGyAMAIBccUULGwBUxWlEcIVIMF4wV0NK+5Y5gSZsQCCkkvQn/sPDCGqzd3JadTtgTY/DNAGoWqArngUgbAAZgIABAMtrbQEDMM1o77loJLReWDPN8iWU4l3YDABxfN+5dOTewPE6f0RsABhm5xDY7htgmM8aW7Dl73rO+UkAgXC0iV3/jSNfNOWkR+dz7fP3b8diEbeGPCT99zlt+VvoOiCNxZ1x1r7yGo9l5WcfjMIlaV4uunVcZvEAN+8tJNw7DvlBrjyma5GpAKAFw0NDw8nkCIDOA6cAYPzh8PCQWCafR5b+BHXjkW1AQwTDcuq8Pjm7uENsQG7xS/ARDQhElHikA8B6ccUwy+LYwQmoxrqeAZDV07ce/7T51CDqKCrZgM6siVobsEAlvN1ImTG4RAOGu8KotQFHFgwAbdKNX4oHvx9QUZH1ALr7BsNFAEip1jrv9EoMFauwODOmVqQ/PRvZfxqAbuir2RxMaBWZYAZPKyY6s2Py/R/fdw5AOnLPx7ejzLe+W64e9tM5lGGYTYIjAAzTMrZR+l8e+RGAQEWfec8GrnsDjUYAHG9SeID5XDXBhgwAPRY2gDKM5V1/n9JfhvR9uXWPyxrU2gA5AiCvEfre0m/H2lBIsgEjI0nxeHh4qHo5f0lBqDfNl87//Mmen737HoDOA6fEVegpy0Xt0t/OzXtP/UcAZOlvZ4fYAMJuA+7OXg9EHLbenW2AWt1TN3RTPLvR1CBbNODefHXI3T/qviQ/5bM8oE1TAVyqTDL+v01URxqnSwaAJTOWqAQEDAUiAiCfrSueTa9EUpW/i7a9pxWg+i0wxUMloOkAEnvMpeWVsPJnfQet0t87AkDb/4Xs4q/+k5oYINsAhtkW2AAwzEbZymwft9PWHQ3W6A1YPICjAah7hxP3nxbzNTWjsgFARfX6kf4emr4JyAa4GQA0kkokbIBdiFcv58MGeOcgyUEGe9KRfESU+VomcDmcMzny1ueHu31EA25PFequIfp7u32u3AKEE6BeQG4IG5B9+k1T1+OH/kg8JQwAQTZgQ6lBdz6A1LgTQDqmwGYACEcb8K/WX6SunS8UrlNkQCAMwCOj3YR5WF1LdZ+v+culj/tA2QDopqYY+bbAqqIGVotRVVWeztwtrq+i2lTXNE0TpgJAgRkIRaEoq0/vmLr5xbPz12fH9g9EAKwHc0YJuSffjIYiAJ6/cNvxn04G4NSFflPX7cvYBjDMFsMpQAzTPNu45S94mNYAnDl+ADYb4LiybsNQcQOOaTw+b1JU+lLGv8UGCE72xoVA2RrpT1DwYXFmtHvVeQdEL647egA7lJwjRv862gDH/BzBfCkBYOPCWe7wg0qeT10bsPhgDIC3DTh7olxmXdcJTM4uYsfYAJEXRGLdzQZEgvHUo68Zpq4oMIGVR78CQLYBgtXH/2U2uBjrecctNeh+5kNUbIOzQzjzCoBFbQRA90QIQFfWPPXYcPzxU1IQKk7gX62/KD/7cejCx1n801jNL9Ujo2xlw3v76S/wVHAdwFSx+susmChBA6CYBQBrpXYEVGjoal9f0gwz3AaAAgKJvudEBEALxShSpygagHv6BTN6+vH4n8RO6PmFb5omACNbWANw8/pZuNsAgWUZ5QWxDWCYLYMjAAzTDP/Nv/2t3MLbdZdtwXAuSwsg8gCOEYDmmgWRDZAGuPqV/naK+TWKAJw+ulcc1ILhrZT+FhKrphj9a8FuABwjAPI8YBL6HqEA1NoAkv4EjQF2Q04xIsT5R0aSoVh6yOVyhKMNoAiAfMRPNAC+AwI7xAYQbtGA1KOviceKAsPQDbOEyqdi24E/pAfZJ+Xxt2pwEYChm7Ged1CJCZxIvEzSn1hdT6kBRVEAILYncFR5y3Izoig5ml5+4VrgUr1RxL+bPwsgiPLfrGHr7fNPY6P/9Z099Di0l/5qyv+Gtkj5L7dPXUsVigvoUjRNM8o/wZKio5IUpCna00/HTbMAxTTNEIBSfs00zH0nX4E0fpvoPny8ZOha8KlR2gfT1EKpYCBgGCWzkmkVC7VB0veffHT+1rsfyREAGbtbYCfAMJsNGwCGaQyaf6kXy1krbjZgy+byWloAkbJ3O2FDi2UycxPey/w09wSwODMq1L8aWoBLss0WSH+CZoE9Rbt9e96nAbDgp5vQxKNMwRYS8TYAkDzA8PCQ+DIUSwPwVv8Ciw2wGwAAs7kjz51xnQ0s48cGpOcnX3n5VT9n2xosNkBW/6gYAHpMNsC0Jc0LA1A+Yc9PAChQVDUAIBaOr+ZTqqYoStkAADCBYETpjw6Jk1z7cO/BPT8QX3ZoCvUDtUC630IQumwA5rScXtwHQFW1PLTiusgaqjEABRjHsaKqgQelaKnyoa8rBi1TKgbgyae3AUApmkYA5S6iCkzFngHYefCkeJyZn+w+FtcUzdRLiqYA0E1dVTVUbICiaQA8DIBgI3lB3/ruN9g2MIx/2AAwTGP82j/7OoADAxFvD0BS2zvfpiVzeYWmFy2APCqALYvfGP7Kxm+AuPKzEUh1vTLZ9bJSpFG+Z04cTM8nxbMWne1H+lMqAslxt4ZCPpcJAwDPhptyba53Jo+3jp94VFObK9uAugbAgiXhxz/CBlgMwGzuCD3waQAINxsgpsa+/sY52CYNby/CBvzoL8uhJ0p5lw1AVGsHkCutGKauqNVuOxYDUF4s2QDDLJa3/xVFqchwUzdVJRBS2lOPvhYNxosrSyUVAPZ3/6BDq1YnCxvwu/mz80YMgPiAPqjlxDJTLwUUfT6QyxbLMRYTEVVRxId5qbCKylZ8MBqMak/oKVXTDpZiAB6UouuGDqWoKAFFDQCAYgJK+XdbUYLaY0XTCut7TJiKUlTUPQDEOSEZAHon6eo9pijFQHTaKHXJ3xmyAW3RDlQMwMBrewwdRrFmmYVGbQBtyohhZGwDGMYPXAPAMM0wP75uFHL7z0ZR+fh3tAFuafctkf4CIf1bvrhRysW1FbUtpH8sEgJgGCVFKd6dfnD29HnUNuTxueWfrs1DsF+xoWUWHDP17W15aNkf/d6/Fp3+5UweC6I81yL9iVC4DbU2wA9NS3/CXhsgpH8TUHmAbAPs33wANGB4h9gAURsQDZbvJzUzqoUWE33noSMaaAdgFAEgGogDWDdyhqmLPXWHEy68DSDa8xPdKALQi6aiQAvCpC02EwCWH/0KoAD6WiENTQ/pWkDBYuoXyYIc3/tDAN/r/PjT1C/lit0hU4Ok/gHM6VFUbMCT4Op6sRvFGAATZZtqAFCgwAQQqBbeKFHtiXyrc4EsgGPBxU8Lq+ulY6ZRUjQTCjR1QdU0AIo2p2oBRdEMxQh13KWbL62HAZhGlAICdCo5KUhRigCK2WOAEoxVbYBh6KoayOWt1cxqMA242gDH8gA4KXuS/ha4nIBh/MARAIZpDIoAADAK3QDIAwiEDXBMtkHLpf/cxNj4tEXNe7QA8tMsqGkoCEAEOg5R+S9Jf4DyCmpyl8+ejvk/uV1W2hNyuvvO+1xGDxKVCmD7JGDHmV8WRkaSoc59ALq6usRB2siX03Ucpb+dU4c6665xlP7JkSR8ZwFZXrhn/wX78YYiADLvXb5lP0gRAJkdYgMAXLt6RQ0u0WOxtS+7RFKolCFTUO5TfMCEaYkAWKAdAQCKAlVTHlwbTPSdp1wbOm7qRQCqqUQNDUCpMttX1QK5YrVwImioqKWo6gDMyl734sxkdeKErc2pquRCoXtBRQGgF7sAqJpG/0wA64Yezir5cOUfoqkAioWOzMNbCKjiG2KapmZqphZEWd/DNKKdB05J6t8E0HXoMEBdhiqRh4oNoOQoNbg4fTUdjLQfeSkcCdT84TcUDYCk7C3q33CJtrITYBhH2AAwTGNYDABhtwGWZBv/o3n9I2cZycrerQLY58qmIQMQ6DikaGEAHe2Vj3mlSP+XDQAp9dffer7uaR13lAmLuG9oDPCpPdWCV7sBqIss6588fiQ/Vcg8gVSke+XKZdTOZ3W4GU/1T7o/M0cZTXlsYJKXTHIkGVASAOL7jsvHmzAA8sCE29M1SUF2A0DsBBtw7eoVeqAGl070VMMgU6kbsg1QA1VxbZTMXHEFgGHqpntMAJINeHT9PBTARKLvOTpiGiWIT15FUU3AhBIIhEzt0VT5z3PPocGwaphGoKjqZkVZa4H5oKmRpF7Ld6ZmJgFAMRN952UHoKq5vcosgEygnDgUUBQAlMqUVwwAWDcQVEJZBUA+pgAwFCOgaLqpK5oixgIEDLUt3JY1dAAlQ+880F/MHi+umzBVAGtLM5W7PQyAbtKiKcLx++KxYqgAohHnWeAWJ5CenwDw1tesFc/Ek4ny3/WBgUoMxLO9GdsAhrHAKUAM0wIe385BsgHRnp8AJ+RkmzvT85dabQCIRtuA+lnZHEL6a6oKVHW/jIea3+Bi/1Drz9QqNTo836j6t+/o79t/CFImz+DLDpKX5rPabYB/6S+zwYG+qMQN0uk0AGAaNhvgk7Tt3s4eD8FmA+zsnKSg/oNxoOY2TiRexprVBhztfFE8nl78EECuuCJsgAIFgGwJRF4QUM4eSs2MasHFRN/5cgBBgVHsBExDoa/MAspaXzWLSw8/VFSlq+8cANMMqIF5AAZQVHQoimZq4XBGUXVFKRpGODUzCiiJvvOKklOASGRqBQDQmY8CyARyVPhrKKYChEoqgAIM1YDephoKVAUADAO6qQNQgO6+8wFDXb5ftgHxcFvnwf6V9TXTBGLTpeJ+U48CaEscIieASoBDUzWd4iSV70Rh9RiAcOxB9TuzvgYnGyDygkj6e3NvVuSwDUKyAW5wXhDDWGADwDAtQ9iAxal8dvn7gfCLm3q5wbMnRJxBiPu6yl62AS2B+v9k1wuKFq5If+odrsnLMvOT9vaFjmyS7oc0+UuQmhlF32s+X+6dzOMnoV/YgLoJP27SX6Y5GyBShpIjSUpeas4G2KW/zDNhA/oPel1X2IBXXvw1y1PHu1+iB59mPqKYgFGWzoolLJBbeFsv5rVyopFpwlyc+cQ0ymXHajADwCh20t65ARNKUUFZVJummZoZ0yITtJg2yA1AUcySUgoEUopSNBVT0dYVUwGQfvRBMHhvT995A4oKE8BKeB1AZz6aCeRKihEoqgCKMCkgoGhaqTz22DQBVVMCilYslSKmFtBNAJEj50smcstznQf7AcQjbSvrazChQIGaoz5Hhh5RAEOPAlC1dQCaqsGEjpoN+Xz2CPzZgOXF99VgnbwgmYoTGDRK5oGzdUqb2AYwjIBTgBimAUTW6fz4upwCJBMIlzN3i2unNy/fhrBUGgTC0TMnDvpZ6b2YIGVvGCXvZSM//lGisrFtmlWJ3xYrzyWlSMiZ/hCA23drygEtKUD+pb8oGpYrie0pQLTMY+AXgJvFI3U78Gwkj59SgKprejvogVuNgZv0H0km4ZTRNDw0DN82IDmSFNUCIgWISKfTr77QXbk3r7N5S3+BvX7am22xAXUHpQm8v8PTix8KG2DxAE8n8wpUwFSDKagLADRNBWAYpsjgN00TRo8aXHxytzIk2ES4bRJAqVJvQItNo1ujPH5TeXx3PWBoAHTFCIXuRTq/BCASf6xWOgsZqq4WFQCdpXIogI5rhlEIQNHKbYpMwNRNAG1aMGAZfhxzSNeZm6sm8QdCUUVRUg9nAPT0HQXQHogBWC2W/9IpqmBBdgIATAUxGkD2JA5ANcqzGoxil1sK0Hs/vS4eH99XjrmlI/cGjtfvwytgJ8DsZtgAMEx9HHtN6MUe2vK3IBsASMk2m2oALHXAdskuG4C6i+Wm/mLb3m3ZwwkagWRKNkAH0BYLZuYnSfdbEDZAGIAmpL+MsAHCA4hlotI3NVPT3me8eIgeFKC5GQCfuh+emTzCAAjpLyPbAI9df1L/w0NDVANQ+9QIGrQBhGwAzhzV7AvsNmCTpL/MDrcB8Pwmkw0AoFecsGli8V45Fy4YuQfAMHWl8s1WoJANME2TVPuTu3mYphaZABDQVHES3Sg3FO059hx9aJslPL2XV6CEI1MH9fbVrtcL0AHEOx6rmpJXdABKUaWXBTQAiOcjsULuSdQoqKapQNWU8kkNwDRVA1pABRAzVLhIf+Lp4zgABEIAMvOTigJV0QAcOuxQ0kNOwI8NAJBbrkYmFTUbCv35q59zGqhcMQCy9KcHDRkAgm0AszthA8AwXjhKf4LmANg9gMUAEHem5zfJAHg09JQlOxmAuovt87zkvB3HNQ8nakarkg3IzE8G1dz5wT0eN3/7bvb1t57foPSXWZwZ1YIRu/SXSc2MCulPOBqAlkh/4sqVy47SX+bAwGF4JvyMJJPDQ0OoFAHbnh0hA0D4jwYElISj9JchG7AF0t/CDncCdWxAaTUaaCcz8HgiF6zIU0INKIZRrSFWoOi6oWrKnkODsk0lS0C9PQ3aqjdMRVWoJaleOKWFJrSAEml/m5aFTM00oXbNqJoSLKkAipVrqJoSMHQFZkGDosDQocNUNcU0yrXDpmQAoGkA2oOuTbqePo5roSgouGeaUBTa9f/iK88BuP7QYVvEpw1YS+8FoKqaopb3CDo74/ZGQADe++l1Uv/p2u9tEwaAYBvA7DbYADCMMx7SXyBmgck2wNEAtKoF0MT9p5acnDtTc26LM/OTsuvwWElQdxELlsT9mjVKEcDDu5+IA209xwCoinGmr76A7jrQf3N08UjPkp+VddfIOEp/AO8/KqekF6VMfYsBaKH0F7jNDgMQipUvZx+2KkMGgFKx7SLVYgCIujYgOZJ8662hRR+S1/veiBZKf5ln1wYQFBOwRJ9EWyGyAaYOVVMi7W9HOmchhapEJk/ACJQUXS2pJaUsoGMdX452zgGYHVsUeUSKqYSgRTpm5WuZAHRd0ZSiZoJmeelQNZSMmsahpmlqpqJqCql/ADElKrc/sv67bi+3B6wOgQyAwO4EHG1AZn5y34lynHAtvVdIfygIx4IACqlZx0Sg8enyN6qkZo0SQmoMGzAAAnYCzC6BDQDDWPEj/QlhAAhhA8gDFNdOt1D3i8eOOTmyuJcH9NjDDh42wK8BqG3vQwagLP1VxKKqaVJlIdzEvRD0N0cXfa70SV3pL0M2QBiApqU/df0fHh4S7f8htQEVWGyAkP6Et8j+cPwhapv9ywN97epf4KFQyQBU7s1L8nrf2yZJf5nPmA0QwjqktANYL65EO74IILpnzjCqGWuqplA5vWoGALQXYiuBtXDnl0zFBBDtmFM0PL6bB1BcXwWQ6DuvQunserKv1A7gsbICQzdNlEIAYCoQwjsgjR8uGSYA00QwWP7zjylRy33KZOYmn+s6K76UVb7FANgXCMgJpObu0JfCAKznilT+G4yqqLyVqap68tXJ/t6ab/LU41sA1gtr9B2jd6lYtM2yrGnYBjCfedgAMEwZ/7pfYDEAxOPbuUBY7T4RRqUV4Ds/+dGX3v5Kc3flJyeHuDM1l7Gl07jlHTnagLoGQFGKim3NUmoFFelPR4QBQK2yt6t5YQAsi1ul++Ei/WXW8uvUwMcP9l1/of4hzf2VD1pYfDBqkf6Em8julOR1UjIY5bPNjHqof4GjQpUNQOXenCWv2701JP0vJ2feGOrzv97OZ8YGqAGFpD8ALfY6ACgwjFJb17yhmFBglAAFmoLMvVHIoYCuL4dMrQDdUMxIx6yqKY/v5kXJcTG/qgCHn+8BEDK1/cvmk3YjZxoK6XgdACjrXyh7U9VUoC0YW86t0UGh/mEzAJSiJqt/Aal8RwMgL6iean4SwGpxDYBuGrIBCEbK0l+MEwbQ99InkUgbgP7eQSH95RMaumnoiEWrf8gtcQJsA5jPMNwGlGGakf4eyEPBqAt4KFbjEx5m/8fDsX9S9zx26W+HdDzZgAPR1QM+2oAS9JK6SUGnju2lZYo0zEv2ANmcEY62BVWHTT7iwcIeAM+fd+6YZOGT0cXPv/2qn5WCjUh/wqf690j4GR4esh8ZsYl1AMFY+sDAYeCwH1nZaZPXTuN+h+BDpPpsGErp/n6SgprY9de0oNtT6blJvZj3bj2ERnqGph6M+SmE8LOMFvj5edX9JlPz0Olg+f6nPnqQkOZCqGogqms5TYeJaEkFYOo6pfekZ8cCnW8DgGkWUAohUDD1iBnI67rccCgYbg/FJlMz84nDgwWUZjoQLELRFNGQU5EWm6oGIBqMAzjU+aJR+sDjn+Yh/YkLh6OdnqZ9BR8DZhwvQgpRtgfbAKwW19qDMYoJRKJB3dTLG/+BNABhA9bX1wCM3r8GyRERNFdBrS1mmZwdgz8bMPX41on9zuPqqG0oGnQC3/ruN9g5MDsfjgAwu5oNSn/HCICdH/15opBdOPv5u+IIfWK52QBv6e/WTb+Uz8E2GNhP5bGwAXIEgKQ/AC24gNr2nbIBoKwGkikisV6OAARDVTt09rQ1aVhEADLzk4FQFP5mAxMbl/4XD4Weot17Um/dRH9L/s/w8BCcIgDU4ceCLCvlXXa79PeDz71qoVDtEQCZRZd7azrh5+rP5nW98MbQEfmgqC0Wxc11bQDhZgPkeclwl+M+l1loVbMgANOLHz64vQiglF8TKxP7Vo92vojx6wCm29ZMXQewZvSXJ3UBWFsDoCgAcLQz+1hZmZ3M6YoJIBiaMBXEOr8MINY1FyiUl5FWDupYVcvTx0w1oGpl6S9PNwOQQPbjxVviS4oAWHJ+7HhLfyL58EogojxXKm8E2BOH6LqZ+UkRFhALgm13950ov43QP0oJWA1AJORl491sAAUTDKnzqbdhqCvr6QNFzCRmG8DsZNgAMLuRVm35+zEAf/EfEWpLFLILg1+8ahTLXXHkjxxhA2bz/3pt7pt1T+hmANbWcgDCAUCyAf5bD92ZmiMDYJH+MmQDFDUwUGnueXmk2gJI2AAyALL0l5FtwM3RRSH9CT8GoFXSnx7LffplG+C/xlds9g8PD8Gm/h2lvwzJShLZzUl/+9nqkjgy6G0AiEXp3jaS6385OaNpQdkAWNoKWbobNWED5B5KlrPJWtznMg9aZQOuXb2SK64CUBQU82u9x187e3x/9enx6xPK/vWgSQsiRQVASQWAUmENwEuFeQCXl4oAlPBdJfFFoDyKLN42h4pWDldqfU1NA7CqIhpoVwOKRfrX3HPFBqw8vbdx6U/82Qf/v0BE/VxPTXxPThwSYQG6NNkANTYOwKL+IUUATAWRUJuh+5Uxsr4n9Y/ad2P7MjuOsl7+TBEGwPslDLO9sAFgdhetzfapawCmn7w39s7robYEgFOvfZ8OGsU9lo8c8XmmF7sBrC+87XHOU8f2OqbukAEghA1oogrZrvs9kA0AAC1+tLMrbtab+JuenxQNQL1Hg1loqMbXEVn6E5ZBXQBee+0Nn2fzpq703zz8iNSR5Mjf/fv/eAtuBhUDAODVzx9w7Cjq2N7Upw1YmH7s52z2SgbHZVtmA65dvWI50n8wTisnZ1cBILsCOMhJerMYyN4DkHowWoy2P97/KoD1So5VV2yupCJklN9YSPqbMYctfzfIJiWUrMcan+o/Mz+ZfPheIKICsBgADz5evBVsu0s2oPt4+QdnMQBtgfKufwGNyRjHDCI7ddOHhKy3fKzYDYBlPcPsBLgGgNkttFb612X6yXuWI2N//ergF68CUINLUE0RDbAT6fkJnGyA2Js/c+Kgd/p+voS2tuh8Dn43sQHUSv/xyQIAkvL21B2H18aPAohF1YH+EOAw9JeQu/5TecDZ03BbLNMS6Q/Aov4tUMN+atfjNqkXld1rGsrruGwbpT9RN3P94eqRnv6vb+EdAUBmbjI9t+p/PcUfPGwA/SACEQAotahE2Ge9hFjg7QQe6z0AEh4rAAD9B+O0mFbKmXUAkF2RRSVJfwDFSHv89GvX5lKl2fFE3/lIsYSKDQgYwAakf/mfZsbgZAP8S/+6azoP9F+dSgEYiKXEwWDs7iuxAHDu49St7uNhsgEWSP3LAYpMTKG8/1YhzubmBL713W9MPb7V3+tcP+C4HmwDmB0DRwCYzzibqvvtEQAH3V+JAFAWEB0Ue05kAywRAIHwAEL6W5BtgIgAKFI1XCwagtMQXwt26U/Ie/mONuDyyA0tflT0/wHwXO3wL6HsLQO/Xn/rebkF0JGeJVppjwC0SvoTdgNAEQC3WV2yvrdsXb/z4x8ODQ0BSCaTpNVCtbrfqWZ3G7Ao1Ier5SScpfTS51894vSKFnM5OZOZn9DUEADdyL/+haP2NY6b8TIWG+A2mIxswEYiABaaCAgcuvlOWFU+6vsygFz7HgA1uT0VKAIgpD8dpJVycEC2Af3LdwAEVQVAMVL+Tb42l1KgACjmV2nx2cLDqR5VAZSODjQl/e2QDfCf8yPUf/LhewAoAlBaN4YOv07HxanIABCqmhtMfEyPqZEaKklBANZKawDaAm30humYnuTHBviMAFhw7EMqPXuucjY/JwPYCTDbDRsA5jPL1mz5Cw9gl/6EbAAAkAeQP3JkD2AxAABOH9ub88wIQsUGZHOugtjDBrhJf8KezCPbgPHJgjxRi3jONv03PT9p3+C3GADiSM+S9xxfojnpT9gNgMeULoEWjNgPUgSAoM6ePsXitpB6MCakP7FlBuAHv//XADZoAIjuI4N+ZhLnV6w/dzRrAAifP9nVP/l/HQxpY0e/rIjMe5jrBk4/P2BffO3qlf6DcSH9CbsBKN9A3/n+3nYAVCIs8/5czQyNYn71jV/4O37uVsZb/aNSnZJAnUgdbBv/dgNgcRFkAFSpk1ggqr4xWCOvZT5J3/auTCCup13P0JwBIEQfUjfcGgq5wTaA2S44BYj5DOJT+i9M5QGUCuaBAQd55x836Q9g7J3XxeNQrKeQXTi+r3rk3txlUEYQAKMmTeC0tOVPvUQ9bIDc09PRBtBBuWcoJOlPuj+bMwDohqmpCmDGohoARQ1YPMAHH5dTONrbQgCC4TbUDtaFlD5EbuHBwh4/eT7BUHRuOTq3nH2z17l6GBuT/m7QHr8fG+CI3NTfZ/bI1nN7SgcGghEU1+sLuNZy83YmfnRw5VPXTVm5trhuB9K66r98toMA8PjuA7dlcrF13Wx+kZlTl+PHn49ryuLMaE9ftSN+yGWcbqLv/GObf3ak/2D8cX4N5F0HLgAONoAwY+0DJw+Kf5GfX0Wf0p9IIQZ3G1A356fzQL9jDEGo/0AllviDd4K/+KWifSU8u5HKXOg6BycbYFH/Qq/7TB+anB2znMHxbP4ReUG/+Tt/bOrF73y7fh8IhmkJHAFgPlM0JP2JUqH8J9CEDbg3d8s0XLubo2IAKAKAShDgl361mjBDHgCVj6Vitv+0S7YPsfFoQFtMQWUjX0h/vdpzzwQA09Q0BUAsqgkDsJYzABiUW1xZQDaAKObXCnqoLVb+hogXFgvlT3ea8yVSfUQEQPQLCkjR81f7amxAq6S/dw2Amw1wjABoQWvtqczNe093QgrQ7SmHjASyAVsTAfj5e+XvkqKoaw/uALj0+QN0xK2tkIcN8JhJ7HE2ygsSr3VsteRoAyyZOd4Urv54f0hNpoqKAgUoVRJyDBPnCg9zF6p/ueUaXwlhoS0RADlByOEexq+jEgEwY+202I53L1RvvNtSCSfgJv1p+x9AIKKS9LfXAV9/NEbTfwPl6b8TdNzNADSBnBck5LujWPdjAxwNQBPSX/DJR+UsL1PXT1ZSidgJMJsNRwCYzwJN6H478+Pr8GcD7s1Vd5UUtejtAbw5efANVGyAHBxww0804M7UXCwacvIABoC1LNpi2o1PcrGoViv9a9B1E0A2pxu6DkUxbMtowepaAUB7WyibM4Ao4CA388UAgHCwJKp+RSjAUfoTV2dy5AH8d/b0s8yb7iPn/YQCKNdfr+iTkeQIAHkiLx1JPdi7jdEAR+lPBCMxAEFlKR7ASp2OTRuloyuynC7nSrUdOQMAyHh3FPU/j4zweTZTD3vIWUvZtCUzxw8l0ywYMGAqpqIq0MLtmSf3C+urX+tNLEr7bHb1D6dImqU2wJmBCwDMzBU36U/YA1Mbl/7lMyMGQJu/WedUB04FIq675gBC8QyApYcN9B9riM6sKQcEPMQ6Jfo3WkzcEvVP3Ju9BeBk77nf+Pb3wDaA2Uw4AsA822xc+osIgMDbA1weuX74VBRAURo86egBju97/S/+I+AZAWiaBkMBNfrdhFbpqGf/VC5HAFB+Wle1QKlklZLy+0YoGi8VcgA0VZGrgUUEYHWtrJQpoSgcLAVDUVFLMHHbKylFtYz3dMK/9Pfe/pex2AARARBlviSPhF4UHsBuBrAdSUE//+lNt9FmAGiM0uz1333ttddpGK2HDfA5ppdW2rX4zdsZAJmlLBSlsysaDEfT85Ovv+FXMFlsgD0C0Oh0Aj+DhN/9m3eqpbcA/EUAFi//aG9QfX+5qAAqACgmTADnV+/ePfaVwRfOOkp/C5Ton3owZpf+bvfQUENSjxCKwP8wCtlIOPYM/bBU1vTCANgjAGIEmDhilLpauP1vJxOrvu998tH551509vwWG7Dw6S/2HP2BWwZRE1ikP819k+FoALOpsAFgnlVasusPJwNAONqAxKr5wys3KguiRZs6JScg9vItBgBAIbvQEgNA1LUBd6cfAFjL1ny0LM6MA0gcOe9hAJTKXr6qBQBYPIDlfSMYrMYSqXgAtQbAMFUAiqKYpqmpANAW0wJ6Nc/n6kwOTngbgM2Q/jLCBmjBiEX6y5ACI+kPm/oXbKUN+PlPy5uyFhtA0v90fBpAMpl87bXyL6qjDfA/pteyUl4mDEAgHEP+ER30bwAIYQNaMpMY9WwAZeAU82vCBvgxAI9+/ledAXVstaQCCqAoOLdy98GJrxqmWTDxwotnRWKPxV0Q5Rpf6R7kG6h7Dz5tgLcBaE76ywgbIOf60xhgeM4BuDqVWi1mAQRLNwB89Qtek31bQiamfPLReSG7n79w223ltasnUJnAqAB7T/wQLZX+hKIuUiqUHXYCzGbABoB5xmiV7pdx8wCQbIBoSiMMAJw8wMmD52BrD/qjP08AWJr58Jv/yKH/ycZxtAFyex9KuRE2gAwABQEsWkRBCahGAFAxAGQVSqWyQhTvG6TmK2vKkAcgA7CWM3TdVCojfOiFSuWFHWFNzvW32wA3A7DZ0l9mZeFdLeiVPQIgOZJcnBl1iwAItswDCANAdPcNytKfkA0AIWyA/zG9Hitp2c3bmWA4+umtm1CUzj3ln3WjBoBYfDC28ZnEAg8PIDfhIRXuxwAAeHL5RxNrJQU4lrmTPvULJmACuolQZ+Ls8f2W3j7iT88i/S33IGyAn3uoawM8DIBP9e8nfej4wV75y7+6864WVN4+4TVfTzQDXTMWAHzttRk/N9M0V26Xq7SLtqxF2QnISn0tt4zKlkk01OZhGLyxq38tuAipfyjbAGZrYAPAPEtshvrvORGm7H9HulfN/bWhANkAEAcGogCOHHbQNMIJ/Mnvrhayi5tkAAiyAR5zfIUNkA0Akeg7T4o8FlXLwj1bEwGQYwWlUklVHU1CDYbUELtcQmCW/xPYbYDFA9gNgE/pv3HdD9/zvJIjSVS6/svRgG20AbIBIOn/+jnrGAe7ASBIIy5LKRg+2+o7rrz7UAGQSWU3bgBai08DgEo6vp+f2uy7f7U8M2bCLAz8LXHQMM1IV7fdAEAa/Vv3Hor5tbPHDmx8SrHjT62F0t9yKqoS9m8ALO2APJqBNo2Q/oR4m9Jr47LPX7hdN0VHrPR5aceNf1L/sA0QYBvAbDZcBMw8S/is032i3wWwTzvtsabnRPWDkE5osQEr6iSAlQ7sR82H7i+89jJ5gGBvCUB7oO1Faku3agJItbvWuoVi1h7/raX94O97ZwSdPR27fTfbFtPk9vvxvccVBfE2FcBAP2nrEC2zJA4Rsag60N8OW1RBJho2AShqCJUqYdKgpfLuf9UDUAnycl4n3f9qX5ScgGNG0A6U/oTc7Yck2vBQNSPIzpZ1C6Vv+6VT9eso7HQEgVobUBdHn3D2eAjA30zdD+3xtYm+o5CLa/381Hrf/GovvvqzH/0lnkzH9x0HEO5MwGnz3jL6ty5njx3weQ/ygroBgY3n/HifqlwlHPSqACYscwAAZOYnfjDv2gy0aRZnxmBLjQOgGYBkAxzFuiM3r59FPRvgLf2PS9lEVAQMQA2m6YHFCYgFv/ob//ff/85v+7xJhrHDBoB59pgfX/fTq8fNBsjSX0bYAJL+Hgjpb38qUc8GbAZi179ujyAqvX00qbT1HDdNKApUFahK/5plJPFzFVEXi6ryMsc1JP1l9kSCADK5IoCAipJT0yHdwFJO11S42YAdK/3dSBwZ/JV/MOgtvxq1AcmRpHAaFHMQ2PuNbkT6y5ANWGqFBitlFs++fOL2tN92rtuOY2sdPz81Ev2FfAbA2sysJcvOV3sfz9vw/5tjaW0ks9nSX/D+nR9rQUV3T7MEcP3RmBqEUewScwCoGejmlQKTDdh78gBtSxil8vhCiw0oH6QUHRVw35j3sAFuOT/E8dpaArHBb3EC8nXT8xMA0sC3vvsNniPGNA0bAOaZxH/Lzif6XeEB3KS/4MHDW2iHx7DLj9K34SL9HdGCC5QFVFxfDUZaIE/t57cf9LYB45OF+L7jcrseN+Shvx5rbt/Nvvxc1D7kKyjN1+yMlm1AQIVZ2fi3oBtYzuuA1Qb4YedIf8KeFOSGTzEnK3755PSl7A26gkArpL9ME9EANyggsMPx7qqJRiR4MNy28mQ6pS3QYvvo36Zvo2kbsGXSX+biwJcpx99tiFggoiCSAZCZnzRKXT5P2yjf/1H5fY/eOVMPFgzdTPSdVwNLqLUBtK6kWRP07XJcxmID/G/82yEnYLEBqZmnYsFbXytBmiPmcSqGcYQNAPMMU9cGLE7lAew7VUf6iwLfa+O5AwPRcEwFkM+WVerV2bFXewdRyf6nBeLZ7cIj15+w2wAa+wWgsytedBlBOj5ZEBN8fUKL5YBAuam/zWK83d8G4OpMjoS+3QaIjCBINsD76jtT+kMS6B67sAAerh4B4CcPRN7mtzymi3ZJrWi9Lwqg82B/54GHVPWbmnFfJs9tnRmDuw0Qhbne/ftbUr+72dT97hE+B+6Sjr89/fjSq6+9+zfvJPp8GYC6JkS+B/82wCetGhRgh5KCUOsELhwa/HjxlugEqgbSADbJBsjvnM91nQPw8cyoGXuzuztDNgAVJ6CGFkMADBw56LArv5ze197mHM4iG6BoVhPusfHvhmwD0vMTauVv3OJAyAaAnQDTCGwAmGcex4wgkv7BqApg8uFYz4mXHV8rpL90thwqKh+SDZAXeDy72dTV/RaiPT/JLbwtpL/APnhIXnP7brYhDyB4s9c5g1/O4Xm1L0oLfNoANw+wo6S/vEPvOADYrilJ+reErmCN+ve4KJx0m6MNqJH+0jK7DbBoercxXl0HTnUdPO79D9lKgpEV72agPm0A3FW4PduHAgKW/p4bvLrHDTRHCzf+PSAnQDYgMz95DCF0n0NlLACAcOc14KWNX0gm3PFBKXcMFekPYLJ0qK3z0KXjXR8vZsQyNbCkBsppnM91nkXWBJCJKSTHPx5PAwBKq2shAG42QKYJ6S/TrYQApKUjajANpzdADggw/mEDwHwWkEMBC1P5fdrp5WidD0679K89YY0NIET5r+VZESKoy/f+zadNNwJqVPoT9+Zurc2d10LQCw67zGQD1rJFu0OgvXz/NkD+fooMfjftLqf417UBP55ctXQL3bj0b7nuJ9FvSc23QxLt5q2V5q4lp/3Q465gzXGPi2bmJr11m7ABdulvX4aZMS0Itcd1pWwDug72dx7cie3mgpHyD8LDCTRnA7wT/Ru1AQ3dADbgBLZG+sukEMvMTSakmqkXus8BuLX+p9U1ZvVdyHHcWEMEovef6zpbygHAZOmQ5bqQHMhznWflF3ZmTQDvPy5GwzFUuoICIBvQ0fXELS/IZ86PI3Kb3ZMHyz/WB5k/AQA472qBbQDjD24DyjwziB6glnY93RXpudiuBELVT5LJh9WPzNfeqr5Xekh/ucVnsLfU3REvd/hxWkD8wmvO78KiDphqAP7g384HI+3NdQJtWvrLX+YWvmQUuy02IJszAFjqAcQAL4GHDfD2UX7wtgEAMvOTid5+AB1h7UTf3g1errXZPnbl7S3Hb09VmyYV16tS5vlzVgGamZvUi3mLkpMNhtjy91b/HiRHkm9+vsnXynhMERb89J0JTQl87os7KAJgp+6QYD8q/LHec/b4/tvTjy3HqRFQQ51Am7sBQWtzfpqW/lQE/PIJh5Iky0VJ3Adjd+nLFGLdx11TN5tzAo/Hy8HJO2uv0APTiAC4dLyr7ms/nK3JfitAB5Ar1ORSyjZA0bQNbvynbT+UYNtd8bhuSRvBNoBxgyMAzE7H3vv/wECEPEB3rfrsXjUDIQBYbFcA9B8ehGQD/EtVa39PF17qOgfg8fj6fh+1yM3RhPS36H5BtOed3MKX1OCibAPWF25570GmKSv39PP2pzYu/QlLNED2ACInGIAJJZM37sykAJzp89k7cXMRyffiS4/FsvQngpGY7AEEsiqypHaIXf8dRTwA+LMBOxwKCGwkGvBY7ymYwcnZVXuKnZ1GO4H6uQEZn3lBm5fu3+hFV2IPASQq0t+7azKFBRq1AfsHyoHE9/50FECi77yiug6BEVikPxEwTADRULkhBDmB5fQ++rKr+4lY2RLpD0n9+5T+aHAkDrPbYAPA7Fw8xn6dOxwG8NhlgBcZA2ED7n865ketfpS+benv6Zbb81JXzRs63UZrbUALpb8g2vMOALIBFE2+PIPUTPmD0LI4Pe8qC1ol/WUsNiA1K0t/mJUxZNl8EcDOsQGWVjyOa+zSXxCMxCCFAtykmFByO036y+xyG0DS33oqFxvQaCdQPzfghocN2DnSH5K6VY7v8T8wpTkbACAY04Dyu9/eEweBA24rHdW/gGxASVXICYiAQGZxH4AXzzXzI/bY+Gfpz7QQNgDMTsRN+lukJ2lubxsA4PTF+pVk1N+zuyPuXddrkf4y3jbgG7954E9+d7XubbQk28eb88/NAcgt1AgC2QYsP7lv2LKAiM2Q/jKv9kUz85NX53OaChOKbjhfbqfZALg4gaHhIQ/1L3j+XLyuFOsKwpgbSzkpOUtXUPhI92+U1MxYwjY4yU5mfpLqB3aVDSAdb1f/1VOFq12DNyj9HW/Az2K7Ddj6dH+3i8ppLR45Px40agNEM9BI5xKAxZnFlA77b7i39JcJVN6pZBsQCbWNT+YADPT7bWfcko1/lv6MT9gAMDsIjy1/D+m5fyDi6gF875fUbf4jrgV3ywEpIyixalIZgBgFACAU66b2RKW8AWD/2eoHwxZI/5MHq+6FmoRa+k+mZkbPne040B+iYcDi+Ht/c/NrLz/XxO01hEj4OX54792HKVSEvt0G0MrY0bPYYTYAtU4A7mNHibMntMzcZGbO64SWXX+7krNIf7dlFjJzk5n5ydTMXsBB+lSXVX4o1CPIbaXjsp1mA8bv6wBMQwdw9oSvcQTeNmBydhWBo8EAZiZueKfS9feWy9ZTgaPeeUGN0oQN0IJ13hU3Q/rDSf1vXPrLiFphP05Afr+90HseQGpmbLJ0iIoB6kr/l3qD1x86/H5b8oIIPzaAc36YrYcNALMjaE76C+y63L/0l6EWnwC8O/172IAnZvuT29inrO4fiAgPYCcQVkt54/HtHIDe55sRBE1Lf5loz4/zmVeM4h4AZ2zDgMkDBOtvYW8UIR+fmGWddPpwAoCwAbFwkMxAxiUx6c5Maud4AELW5XYb0IT0l/G5oetoA2hlMpkEkBwZATA0DNjEveO32m4D6i7bCTaApL/M7akCNmADJmdronmqqqUf3TYM3W4DhPQXL/FTHtAoDdkAb1qu/mkM8K17c0BZFh+KrbVW+luoGxBwbAYqnvVW/y/1lv8sLxwuC/rrD61dj0VekDiSmZ9Ev+seSkuKfVn6M43CBoDZZjYo/WVakoXv2ADU7XKyBxDilaCngq9EASzNPDKKPfZhwGpoEcD8uK+RxgL/0t9N98uEOz840vU1x6c+59LUv4XYpb+MsAFn+hLX3r/mfaqdFgqwQzbgc1943qf01+slIPjc0BU2QJb+Q0NDyWRyaHgYNhvg5rKqJ5zxd13PoMHWYJf+Mk3YgNtTzpYekg3IR0KJvvNC+sNmGLCZNgDNOoHN2PinFkAXB7586171N34uryB/5kjiTsulv4y3DXjpIMn36VLuuFD/wXCbT/UvQ07AzQYsPrnncULe+Ge2ETYAzLbhM9F/66FSYO8WQMT+gchTs33eFgp4YrbvU1YBFD/IZRIORkINLqhSB966I42J1kp/ACfKjaXvA6AtMaK7tqm/d2P45vCW/jKXLl4au/dImAEKBbixk23AueMa6uVek/SXpZgQc8nkiONLtGBkaGio7tWF+rcvFjZgaHg4NTNWV9k3BNmAX/rqNkQDLv/sph/74d8GjN/XFRUATMP5ozMa0gCt/2AcpU+BQThJfxm5PKCFNBoQ2KScHzuqVpXjc9mzc2M4Pzi1qVd0tAHPVd7bqRmooq5n9U4AHjX2jtJfxm4D6C3OQ2NtQbHv//zf/5nP8zC7EDYAzFbTwi3/1iK1AArnswa66qx/WlGuJNwtNkB4AEINLgBa5YEzdW0ANbEWnewc8Sn9CfnOA9H73aummR+QF7Rc+r//qADAMHS9kChAOxTzCi/II2YfZaOQYgLPlg0g6e+NXfoTJOb++Pf+NYAh2qWv5Wfvvuco6x3xWEY2YJPYrqQg/1EIbxtgiSQoagm1NiAa0lBb45vylP6EHCVoOX5swLZI/2CkuicyOnYCgKIFTL3kYQbGxk+beglo0jBYbMD+geiV25SQYwDI6nF64Ehd6S8j2wCj7aC6Vo17dFbGCaNFOT/gjX9mY7ABYLaOHSv9qQGo6P5Zl6dOm9aONgBA96q5KFUC/OjPS1/5utffnR8b4OgBGpL+MgcGIolVs5yzFLtDB2MdznlBTUPSnyhCW9ODqMh6uw3octElwgZQXhAJfTc22wbY2+9Ynh0aHtqI9JdJ9J0fGh5yFHOUzFP3KjuBZ9EGeCQRCRsQDWmy9KeOQN6ycVOlv4yHDdgy9Q9ADaYBaJr1jzG7Xv4+GIZOZsAi8cfGT8tfOq7xiagSvjt+kh7k0AEAMAEoahGw2r+G1L/gwuHo1alUPKyu4CAA2QZgagIAojWJZJzzw2wLbACYZvjn/+4b/8N/3cB8wdZK/3IjnYLZkqR/0QAU7s1/BI7SX0YMKfOG3ug9Vs6Pr/sPBTQt/SF9/+mbuTiVr9RP/yS34DC8swks0h8AUBZVeV1FrQ1wk/4yj7JRCgWQuPe2Adfev3bp4qUmb90H3qN/E0cGPbZg/Uh/y9nge0+3bgZI54H+RN8giWPvZeUTeq70uQzbagPOHNVuf5rv9uzYg4oNUNT65m3gmAaYiwE8WqvTDFSwZdJfxvKbs5XSXxCMqEAaAM3KFdIfgGHoAFazUQBX3h9sj+XOD05ZpL9M0zZAnHMtW9XgaoCMXM3K5qS/hXhYBUA2AFLeY1fOBJCOKlzsy2wjimluc7418wwh63hDB+qNGW/5lv+i9N5XKtQo16b54ZUbAA5UxLTwAPIIsLq63878+DqlAAVCCkUAfvwXWjDSXsgu/q//aZu8zPs8sg24PHJdPI7sLwF4+dyrjd6YwOePwG4Drs7kaG5XXZykPwAYhr6Wq/4oM/OT+w6dCISicNmwH7v3SP6SVloW222A+LiVDUAwlvZz536wTP6y2ACLMRDaizLsG5X+8mwB+YTJ5IioAXA8m+W6BK1MjiTf/HzlbJJqFysdE8DESp/LvNlUG3D5ZzfF4zNHa9T87en6NsDbAAwcqz5LUYK1rC4m1gFoi1i3k7dF+u8cphc/FI9XVw8AgFnegiQDIKNAAdAer76BUAqQI36cgGwn1rLlNxBFKSkovw22B8rxgZZI/6tTNW9HWT0Y08pZiwOx8lPBWFn9B877/QhrVP1zDQDjAUcAGF+4Sflvffcbjh5gU6W/BdF6fyO4zQFoQvoTBwYie5US5dVQFtDf+98H/vB/cliGeqEA1NoAkv7RDZQPNvQjoIkBZAOEoKfWQG42QNb9qJX+FkijK6oqNL13Q0+xTCxGxQbI0QC3PjYtVP8CUuQ0/8s7FAAg9WCsUelvv4r1qaEhj7P53PolIS5Uu0fth7zS5zIPtiAaYJH+xNnjYWDCjw2wY5f+2XUAMKCZRgmmqWoOV9zl6h/A8e6XAEzOruaKK+VDSgmo2gA7qytlE9XZPWeUTAod2KkbEJA3/sVBRSkBMKFEAu3BSkyyJepfpvyWlStl9WBmfjKmFXEiIaR/OdwqlQe4wRv/TMthA8DUwUPKE9/67jcghQK2UvoLvKfw+keeA9C09JfZPxChpBqlUgYQinUDVrnvxwYcGIhE9pei4Tag+SYtzf0Ifn7rOeAxAGCPfNweCmhC+tufcszdt0h/t/X7AymaHmBhM6S/zNDwkFDnbjagK4iuk357YjpO87WfOTN3WC/W/wPxmAhWs8x3y06fK7fXBjhKf5lGbYCb9Nfl7BFFMQwDpqmoJaoSZulPiIZI0WAcgGwDFEU33WyAWgSQWeqBiXjHU1QyiOx4lxDYpT+ASKD8oylCq/yY/I4T9oP8rkXveHt6D91dB9ZfGEx8bBlW0+luA5pT/7z9z3jDKUBMHX7tn33dMRndFrOFW8C85br/1GMDwJpuAnjQY1WQjdoASgESvNR17onZ7t2Rc2GapvmadRt37q00AnKbCGbBzQMsBSeLSrYt2l6orVI4e9Lv/uUGpH8NNDXMErJ/tS/qlu1jJz0/SdNY5U4+B486N131TvKxUyrkqJZA2ABFLb3x+eZrJLyx7/oLDyA/5THSy47oE0rK3k27+1zmgZwCtAVsV1LQoo9umLO5IwFb81NLCpBQ/67SHzCN8n2TsW2LKGdPhNwGCe8q3Nqhkg0wK+8nwgZQChCpfwDRQHuuWD6Dtw0gLCUEcs6POCjUv92hJTZsAyz9QJdzJQBQjEOHDwAIRMsfW28MunZ2JiewkY1/NgCMNxwBYOrj3Zfm3mzN5+spaWtwk6Q/0aYpa7p5ZMFArQ1oOiOIpP8TE3D/J5P0F/js3+8fx1DAUnDy4Z0UgBMvtYdiKoBCvWJlQdPtlezSn1CDSwCMfId88OpMTlU1eEr/bEE39NJL/fvG1g/IGt1/Q08/Jb95XZ1aaQtrBlUJT8w+8Vi8GcihADQr/WU8pvnWXbaj2K5oQPeRQbjbgNncEXogOv9QBbCMH+kvENJfnC09f/X1N87tWhvgPQkhGoz397ZTecDK8t5yWo4ZENIfQDTQDiAabAeQK66uLO+NdzyltkIe0QCl8lZkV/9C+sMlPpNCDBuzARcOR68/zFVzEZXqr4tQ/5n5iR/MB3/xS85vgKXRdQDwzAtimI3ABoDxi6UvjaphwumznA6+uqeZPVc36S/rfsGleGgkXV5/ZMGweAA0Ego41HkJwBObVJb/yRbpb1mGzbEBS8EanTf14UJbtG3/QNSPDWi59Ce00CIARV0wSnv0YjUjyFv6A4iFNMMoy3dLU/+6t9SEDaBLDPb7GvLaNI7ZPnTwo58n/at/7+lgsE3zrbvM74W3indv/hTAm89/YefYACH9LZATIBvQkPTXVBiS9AeQlmpRaJDwrrIB3tIfkvim8oBp1NgAVKS/TH5xHkC8o/xz8bYBAGbuTAFQlCKARN/5utJfZoM2oD/wCJWxAHQDUIKy+gfgpv7FR2FX1gSQZhvAbAKcAsTU4df+2dctR2Sla/cAwUpuyMs9fj2Azy1/waV4jaoTNgC2jKC6HkAk+nvk3wfCzm++pbzD347FBjSaAiQQQ39J5VMEAEBbtFz7Sz1AHRuAbqr0J4ySWXmwZ73YA0B1ygAT0r+82NABUP+fsGZAmgBA3T/rJvnUzQiSmwvRVYKR4OCpzbUBFkj3Z+Ym/STneAh6e3K/44xetxqAutdNJpOvvfY66iX0Z+Yr/5B6y+hmHJe9e/OnoTAunvmCfHC7koI+ubNiOfLcGS9dLtS/m/QHoKkAEA1VU+Nk9f/6GzV/p595G+Bf+tuZXvxQDSiFlWP2p8S39OIrr6C2rRAhOwFFCwB4ePeOOELqP9F3vrmqDP9OwN6E4OPFW+nlfQCOnu5YelidBWk3AB6fho3aAE4BYrxhA8DUwW4A4OQBgraSAMLbBmxQ+gtkDwB/NsCxxtfRBrgZAPjwAHulYcA+PYCQ/gLZAwgDcOLgoD3msAXSH8CLXecA3FgYK1R2/Y3SHug98ppsQRe6XyAbAIJswODJQ/IyDxuQmZ+0NPW3LBYnz8xPKqp68OhZmtYEYAtsgJD+9KUsze1yvO6u/wYNQN3rCgNQXmkT7kLH1PxD3JfJKy3LHA0AsZU2QJ7qVcxX9ZybAfC58Q8gFgEquexpm/6zGIDyDXxGbcBG1L+FiYdpemD5lpIBIBxtAKl/LbT46egCLDk/B+PYQJSsrg1wa0H28WLNG7tR6oLNAPjpeAHfToANAOMNGwCmDo4GgCABSqLzxoJrMZOjB2hI+rvpfgseoQBINsC7vU9DHsDRABD0zZENgMDRCdh1v4WpDxcAtEXbThys+eiSfwpN8+d/pcIm2iy6HxXpD+Apyt/Dewsf0AM1oJTWyl1rTh3qvHLlcrdNKdoNAHUBioWDaKqpv339Wi6//KTaBkQ2AMQm2QCL9Cfs0pxkR13p7/byJgyAfF3LpS0GANIvgEXEOPxD+gbty+wraRnl/4TCKOTx5vMOHgCbbwPcBvqSDbAbAFn6A3j66WjC1ilIlv4iWejm7Ux23TBzc/JKRwNQvoGttQH0C+A/NtVoifm1q1cA2L9XRBNb75m5ybuP0paDsgEQyE5ADZTfYx9L7+ck/cvH9Z6zx/c3ejMCRxvgJv1lLDbgq18ob+j4lP4ydW0AGwDGGzYATH3cPED3qnUWr08b4Phm19CWvwceNkA902Nb7ozFBjgagJ7jYf9jvDycQF3pT9z/eDEajlnUP4DuVRMbboFKBoBI9A06bvkTQvoLyAPQJ+7xrgt08MqVywAsHkA2APYGoG42wPKx6jHW99r712BrLmQxAGi1B3CU/gKfIt6C2zRfy2vlPqF15/5aXmsUosmRkddefw2AGsp7rISLx/DvRm4vLYTCALwMALFJNsBN/Qvc+nsKnn46Wrn0ebhIf+Lm7Qw9EDbAQ/0LtsAGyL+i/mNT3ivtkAEor5dsQHNZN/KdyDbA0QAQZAPo7eho54t0PxbpD2Aj6l8gbIAf6S/z8eItmgH8xVdeakL6y7jZAFb/TF24CJhpmG5ps9lSbvtyzzk3D0DHyQZMhCYAnCqcoqdaJf2J4a6wpTj4idjy912t692Yv+d42M8ySGXEFHaw2IDEqvkX79/YXxlC7M2XfuHzlgtZfhAbH4MAQA0tpB//FAB1RveW/sTJHtcP48WZMUg2QFU1w9Ade/8DyOaLsXDQ0tQfQMbfnY/deyRXFXs0FxqbKKAVNsBb+jeHpfe/ZYyX98q6HoAwCtbfN6MQhs0GtJDUzGgwDD+99uuWCE+uHAFAFjAeAOrZgLrSHy6Vvm5kHo0COHzqPGzS30IsoiJyKLvuq2HXppYIN1Q47rFY/IL5DAikZkbRbM69/TZOH+qiB/aAgAzVE8sI9f9Y97sB5BOqEtbmb9ZdKROM3X0lFgDOoamNfwtUJQwuFGYahyMATH1EBKDbM89EFqDeoYArD8vbaX9r5qR9QdPS38JIOi8066fdVtHps2kPaW4RARDS322lG+JyI+99f/j1rwkn8Bfv30ClotcNudJ3fnzd/0/BP3/+V6oaWpCPvNR1TmzguUl/DygCINPdN3jqUKfI1fEQ6CIUMHbvESqFwnKzIMcgAC2W12fzRccIgExzNsC/9PcfAag7Gzj1YIxe673SzQbQa2X1LyIAAvIArY0AvHszCUCsje877x0EENhtAKl/AJfOWYWy3QY0JP3F+ocTDqk+AJ5+OlrZ9S+/FdCUsW6bFBYRAEEwHIXUZrQurbUBjr+lbmljPn/0hKMNkCMAkMS3/ySiun9WjU7Rpr8Ii/pvSQTAcqsJpX6VsJgBvEkIG8ARAKYubACY+vzaP/u6t+gU+PQAmfxqdz4mvhx6fBKt0/0E7fonMzWfXhYb0MLGnYSfjKCR974PmN94Y4iOkAEg7DbA0uRHJPo/rnehJmzAD6/cKOWOAXhJ2vV/YrZ3H/E7a0xGNgCneqtDA+hsbjaAIuliKNhaLm9pFkQ2wNsAQPIAly5euvuo/igA/zagoV3/zoP9djlu11j+BU3qwZjfzVfbdRWzy3Lkw/GHb771ln1lsM16ts4D/XY57vAPcVpmMQDFPN58fsj/yGE6oZD+hN0AEGQDmpP+xMOJmlQf6TZGUVH/9gHDsg2QDQBJf5mttAH+09KIhtS/wPILKQyAnHXjttiO919Wo9Jf5t2/eQfSj3WDBsDjPt1swGZLf5l0TGEDwNSFU4CY+rx0X7fX1DoiZwRRto+jDQiVkA5luwplD3Cjd+o3VgZadbdPpBrfoc4wJBtwdNGQPYCf/v3+h/7CR0bQndkPPF7+eDwHl/6elhpf+g572IBGJyEQFw/GyAPI38PFB6OoCPdGkaW/fLYzFRsQCwfJA7gl0eZ1FZW5AYdiudOHE37mBshzBkjcU9qPG5d/dqvutOBGpT898MjhQSOCRlzXZ6d/+bpGIQJAk4YSdB7oB4Dxh453KGcElVfWS87xuQzAm88PiQV+bMCnBXpn8NWBcfLT5qW/BZG+Qon+6y7Sn6DxArINsEt/gsYL+LEBG0kKam1amjf2X0hH6e+2WNDyjX+Za1evBMNtkH6sTZ8KTX17t1L9A7g4Xf8PgWE4AsDU5//xX36NHvi0AbBJT4sNyK1VUuEDyqFSNRSwERvwxLO3D2qjAX4yguTJX6Lbj/+ggcUGZDrKO4uznz6OdGpfH/wcfSlHACL7S9Fw29mTNR9O3u19WhgKoFPRt5FsgB3/NoCEvgfiVI6Vu/TA3tQ/EIrKVcIycgQAwFrqEQUKgrF0dY3NBgjj4WEAmpP+dkj9+EnjqblDl4pM+LABRj6KiujRguXfBCHWk8nkm2+9Zbk9yx2qQYc9YJLv5WUH3P+9kg1452oyEMAXLgzZl7nZgA/vWUWMaNzpFgH4SfImKjUnJdvfjSVl31H9iwgApP3+7iODboOE7TwpnfK5cjOiAX5+Sx0DU3CJTfksLCEm51Y81L8FP1UH4jb834MjlsSkYn7t7LEDTXQC9fkmIAcBtlj6i4K6f/wHf7GV12WeRdgAML5owgPAPSMot7Za6dKGkqYA2IgNqCv9BT4zguxDfy3tPhuqHxDSnyADsJ4pURZQql25PHKdpD8tEAbAf2fPltgAKlOWfYujDWihB4CkSuXKXUcDIEqH7c2CCGEA1lJVJ3Dp4iXZAJRXThRgizk4GoBWSf/msF/XMSXDUceQ9K852/ykRaxbDADhmGXkaAN8QjbgnatJ08Tbrw25LZNtgF36yxTzWW8DQFhsgL1g9/LPbsJmP8gAyKk+NDD4uTNx/x7g9nTeT8Uz0VobcOveHIBDsTXHZy2/oh49prxXOiIaazbkGbybYrXqb8qtMgEtLU6onlPJYsulP1j9Mw3CKUBMYxxZMODbBsitaeSMoGhbO4BidhVAQDcBPApkhQf4TnzcpwfwL/2JuhlBbv3+7SvreoDp9A0cAFCTvDD76WPLsgcPb+05EgZqPgUbbeq/wYwgeTCCnMUUiN6HzQb4zwiiNX5sAADK7SFxP/fpbeEBYGsYam8WJJClvweH2x+gXnMhkv6XP84M7nta94RbIP0dSSZHhoaGLZLdLv0Jj616GWc7UQyjWRtQVthXk97LUjNjib5Bb+lPuKl/C6ID1UsnNY9OQZZkJLv0F1CGjx8bcPZ4GJiAv2hAo0lB8OEEHmXbUGsDHH9FHfPT/K8UWOprvRf7p+V/VnBKT/LT2mjn5/w4dtJjGG84AsD4QkQABC0JBZAHALA4XSipeP7IHvlVHjagUelvxy0jyOIBTs2X31izhtlQK6ErV96Vi3ppmi9t/9OR9Uzp9LlyIdpavnyVgI5Xe62fQ/5bfDYaCvCYiVY3FIBWRANEBEBAoQChVv00CwIwdu+RvVkQXCIAH49ljiWeAhibrGYEiQhAV7Bm8eWPMwDcbMCWSf9kMglAL7r+fIeGhrv2u/ZjdTunPQJQl+ZswDtXf2qaePmQcx/GcnPPc/GfJG/a58fJvHTSq/OmHAEA8HJlsePcAIoAyLzx+ecv/+ymo/q3TArzHw3A5iQFwcUGUARA5lBszc9vKfWY8rlS/lJW//bK2kbHUxAt/7O6dvWKz9wkiw1oRvq33YWPgcEtxK7+OQLA+IEjAEyTNBoKgFNxcDDWvjCdL2XXAAQMdObMTLSqvx1DARuX/sRQZ1gOBcCWESSkv8C+zLuMWC7qDcVU8gAy8+O5AwNRAG1hFUA+awC4OjsmPIDoEu3TA/gPBXiPQ4aPUAA2Jxpw+nCiq/LxT1XCcLEBdFA0FHqUjfqvEr6f2gtgsL/GBlikv8zYk72otQHbtesvGBoaTiZH6IFRiBiF1hQ41mXj0QC5NsDS3ge22RECb+lv4eXaxfI2v2M0gET/J3dW3vj885/cWal7fv/RAAD7Aq2PBsBflXAwHH2iR588TJ863OV9Nv+ZMGKD309bfXFanwGBzdj1h2ddsgW5TLlp9Q8ghdgWeADe+Gc2AhsAZkM0nRF0dPnk9cpQ9ECsDQDZgM6cCUDYgO/ExwH8xspAq3S/jFtGkF36X4qHPNyCd0aQsAGhmPW7tGwsYxwAyAaEYyp5AMfpMP4b+3jbgCdm+5PbAOpnMcG3DfAZCug+ct7bA3TVfvzT7r7cLEiGkvhjR8+itlmQPA7MG2EDuoLodFf/ArIBb7zQWX9pI/jRGUNDQ50H+5MjSQDPn9wrjr/1xi8atYXN/m1AZm4i9aDbj/KzFwY0agMCARQrP0AS4tdueels2QZsRPrLyDbgr0bK2//2/f6VJ9MA4vuO171WQzagVMw/dyZOEt8b/zZg/L5uGotnT4TsNsDShmjiYTpXRDSIuk7AD5OzqwgcDQYAoJh3rjew4CcvaJPUv8+ry4iZG/4R0r96ks30ACz9mY3DBoBpATRw189KUqWBkALgQvc5ABYbQMihgAK0fxWfAPCry9YRjy1BtgFHF42YWpMCJKYTeNQPZDpGM7M40+uVgPF4PJcz027Pzo/nABwYiK7MF1/qOmt5NhBSSoWaCQDN2QCLifLTBZXYgsKALvfPfmEDUNn199MzVI4keBBU8Ghp752lR185WHcttHAUwNXxwqsDrZlZ0Wh58dDwEIDkSHJoeGhh8p5buj/q2QD5G+jdV9S7/ehGogHLT6a7+wZFYx9HjobGAQB+N6c91L+g3MJIwcsnteWiNdVHINsAS/6Phbo2QL4Eyfq6NiBXUG+Mlwy91BZV3ZyA6GJ0Y7xk6E8BvHByL5w6kOYq1mstb350b0mBHgsHmnYCk7M148ypvWZzNkCI7M2T/h5XbxV26S/YJA/A6p9pCVwDwPjFXgZgx6cNIAMgQzbgKxdfArA0XlaHBVPL1I433yQPQJC4FwbAYzCZsAF3+8bWK/2M7AbgypV3AUR78wAigQ6qABY1AADWM6XCmtET76IvX+o6Z//OEMIACBrq7+kdP2mut2lLCgO0YMSPTCfSc5NysyCCyoUtDUMVVRUVAo41AACCCgCsLpXrhr8y5NwGlGoANKe27huxARvpLGTko1QSAOD5kz7SMGptgFD/lknAHtnPftqPetuAn17/abGIt1+rzgAW+frCBlANAB20S/lGZ4d5MLly5NK5+If3dLqu3DD0uTNxx9oAn5dGrRPwLiRwtAG5QvUt1NDL6UoWGyCkf3YdgCmv1A3Eo9VglpD+Bv0bTdMwyis1VWnUBlikv53+3gbitP6rDjYJbyfgMwLgof4FLfQAfqQ/FwAwPuEIANNK/IcCLFzoPidCAXsGzj++fZsed2ZN2QP8fseH2ORQwLWVQt2ZxEOd4f+po9y/P1IyAQgbIBPtzUcCHZYOPxZI/cvDd33iMxTw1GxXz7Qf8BxP1sJQABrMCPKzDEC6IkblZkGOhQGiZZBoFqSoJcugX4v098ZR+hNXxwto3AZsUPrTg6GhIQDJZJLEPe33uyGiAW6Rk/Kyyh5/3TtsbTTAkvTvtovvf3aY9zAyUXVQva7NBsicOaotPhibzR3xjgMIKCDgp5DAEg2QpT8kTQ9gLWd8MLbeFlUVtfzNybr8NWsqsvki2QC7+pdX6oa5kit+fG/Bjw1orfQnmmjD31o2GBDwI/2JVsUBeOOfaS0cAWD84icCIPC2AW773N0nwnJxqjH+vni8laEAb/5gz0ficVqvviMfPXJRPJ5O30Cl84/gTO8rI+99X44AKMvxS3vOyGv8RwBk7DbArcbXwwYQLYwGNDc82ELaRYyKUICIAFi6hQraogoq84BFX/+rd6ybr24RAFSEvgeZ+UmPl1eXtUL6e+BtA+wNlywRAGml1bI6zh8gfEYDPCIAxMsntcmVI/3xB24XqrloU9EAueBYjjZAikKcPV2NAFjmAPi8IqQdejnByfsMN8attcmyAaiiKKpq2bYznRcrimFAkRebJgARAbAQjwYdbcBmSP8diMdIBEf8q3+Zpm1AQ9KfIwCMTzgCwGwKjYYCjOPdAJ7Wqlx14KLwAJ1ZE8DU44oU627FXTaF3NunS1MBaJma5uWiAShV/co2YPj1rwH48z/701BM/YUvfx2AcWeh7hW7T4RRr7eP8ADe7X0ODES8PYCfEQfiVJCiARvpEeSIm/QnRKXvmb7EnZlUWzTs1jB0LWegMvzrzXOhyx9nBvfh1TMhuwdwg/b4HW2A9556ddlmSn9KBxoaGkr0nff2AJvBxqMBtOVP6tx787560QajAd4Fx5CiAfEANAX9Rxw6gfrBMl04GI6h1ga4vYTmD2TXW7YfR7+Zpl7SDV8V4Su54o2JpxYbsEvUPxqJBjQn/YkUyrNuGnICvPHPbBJsAJjNwmeDIJL+bqgDFwEY4+9TY5xOINPmvEe+xZANONcXAYCAmi4Z9mctDUDvzH5AdQL7ByJasPyv8O7YQ9JfrPT2AE/M9kbTeBzxnxEEyVFsvFWowFv6y5ANsFcJS5QV1VrO6GxTr44XVotBaubz6pmnAJq2AVsg/eFv45/SgQg/GUGbgZsN8PYAsvSXabkNWH4yDaDDs7HPyyc1YPzarSMUi6h7TgsW6S9DNsDPS1piA8q/mUr5HUZTkXk0qhtIHK7/jRI2QLHGGax8ZqS/jLcN2Ij0t0BOoK4NYOnPbCpsAJjNxc0GWLJ9PFiYziP8vHIW5u33AXSumQD+Da78o26H7IUtI7FmQmrk3xVQRWT9tdfepPLfx+M5t1CABYu4l3W/ZRmc3IKo8W0um9+RbSkM8C/94d4zFDYbkJmfVBR0njhNX64Wg6j09GzCBjhmEDniR/37l/6Z+UkaBFZ3Q9ePDfhw/GHnwVM37z1FbV9Rjzusuz9qtwEeoYC6OnvLbIDFhyT6BpeTNzv2Hae6HrfaAIGH9BcMHKspbPB+CdmAVR9tdWIRAIpsGNx8aTymFFO3VtaMrkP1h6yv5IpAUVPVtqjDG9EzKv0zc5N6Me+n8MAx/6eF6l/gYQNY+jNbABsAZiuwZATN5tsM09cG8/ij93tQbsGhnL1IHgDAK1P6dmUB/ZP9r/+Hqcviy1va8umTX3RbLEIBx7teRlfNU1fHf/jqwC+IL/139ZFtgGN7n51pA7xDAd7SP9h2Rzwurp3x3zM0M39PBAEsyDbgK0N+W/tf/jgD7H31zFM/HsA+PkymIekvf+mz07+bDfhw/CGAoaGhZDIp+orCyQZY7tBnmoTb0AC5AADAjXt6d1/MOz0Gm2YDcO55SAXHdisi3IJTeX8Dl7ZIfzRgGLT03ORk6nD1qFK9lVhEXgkg8N7lW9mcg2okO4FySYMG3Ls9nV9ZM+r+/uiGsbyWy8xP9p18Thx8FtW/7MN9Nr2V2QzpL2O3Aaz+ma2BDQDjl//mD7/fUB2whSMLxlO0i975/pXlQugmgJ7C8wBO77kAwJSKg7eFowsGgA+/oJvRDqBOksaxrguYx/y8c279U7N9r7KKyvAvKvb1YwbUMz0A4KndG03jae2pfBYG+Jf+AHqOh4H7wP3c4tserzrTl7j2/jUAsXAwm/dS6mt6uCOm+m/t/8YLnZc/zow92es/dOB/irC39E+OjNQW4yYTlW+jnAVkwWIDPhx/aF8sbIDwAB7NGf3YAJ+FASLzfottwMsntdTM2NtDz6dmxryjEMIGxAOAyxRhj0s3tPFveQn9XRyP3wMwvXJSLLBJ//LKs8dDAG5PF2QbUKv+y5w9HgZwe/qWtw0Qv3vUY/eFk9tXd7UBHDW9+O2Vf0W3Rf1XbwkxAKfmjYSyoX5BXAHM+IcNALMVPEV530ien4VGlGUWN1+YL39WKQMXt9ED/MGejzJvlMxYRxhAyXRsAEoc67ogf+n2j709RX27g/tQLrmTi3rtyKlT3tp9Z4YCULEB9r40Mk7Sv0q0+yceHmDs3iNRJdwWVdckSdTZHsisliA1DF3OGmi8p2ejGUTeU4Tr7vonR0ZQUeoWbt5bSCaTHh4AUrhg6ICrsnc8uesJn00bIGf7XPIdheiPP0jNINE36N8GbFz6y5RtwGp/W0XQ02L7SmED6EtTr5H+tSu9bID49Uv0no6FNQATD9NAawYJbw0WQe/YyYp+RRsd+rtJ0AT6lBkDsEEbwDB+YAPAbC5C+guOLhoAfIYCBg5dfDBd1vofHxgFQDbg1Ytvbs79eiEagHbGu0QD0IhTjrBF+gvKCrtiGRamaz6TnqC9ZJr7lFW4tPl3rJrYJO3ewlO52QA3vKW/INr9EwBuNkDMAw7F0mOThYBUhOLYMHQjNsBPBpGYImw5f13pLxgaHqYaAAvPn+xJjiSBIZ/33EL82wALRjEMU4UiddENjSMEP0N/m7MBbgXH3vZDHkogTuhoA1aWiwpUKEo4V5p/cuPRteKXvvEGNiz9ZY63T6IyZ8B7MdmAroP9HvOJKyutNsDy60fqX/BM2ACflfc7B5L+MmwDmC2ADQCzWdilv4w9FAAXZSnPAotrytShsVYNARCC3tBN73PKvf+JLk0lD9C96mAAvDfmj5pDH0/9qFQwT561PhUIK0/y5e/bPmVV2IC6BdN+tPu2ZAShERsgS3833W/B2wbMrgePxTDYH+oK4uqdya8Mnbs6XuiIqcsuBdmN2oDKNDEvA2AfJUYZR/6lvx98FgZsBn5swGDXIXttAEwVABRDFARf8n9R3zZgcqV+Yx+yAR37jl86V+3W7ziSzNEGrGSKiqKG1kuqokHVwodPAPjwvUz0YP2Mebe9fNdb9bdpTXUy5Bb824Bsofo7r6musc2dbAM+A+pfwDaA2VTYADCtx1v6CyyhALgry86sGdcUYQM2Pg/YLujdzmlfSXSvmd1QAKRhrt661n7OKl3qKnK3mV8CUeD75DYO1G/dUb7oTgsFwEdhAJqS/jJ2G6BU2jLdT+0F8OL+pzSrS+7m6WYDZqbu9p047W0D/AwSdp0ibKhXb5WAlYsny3KzrvQfGh6m4t3Ug1GRq0PFu5Cyd7bXBjTRJujFIxEAk5kDUJvpfeln6O+lc/GfJH2l+iw/mU7FtUTfoNs0YoFsAzLpnKoEAmvrpqqFjpST9dVIRDfr/IHX3fj3mL/mgb1E3r8N0ILhShVB/W7LO80GfJakvwzbAGaTYAPAtAyfut9C3VBAXCt/FMmhADRrA9wEvTinOKGH9Je/7AqoANyygt2UdKlg1jUAMtuextPCU1lCAU1L/4XpfClvyjdANqCUe0WpNmVFUMHq0qOraXzlYPW1bjbALsTt9cF+pL+4inV8mFGTffT+vRUApUIO6Di3Z9njVJ0H+il9P5nEzXsLqQflol7HxH2fNiAzN5F60O2nMaJP/LcJQkX6T+UOlI8azc/3cLQBli3/upUGIkfoEpDoG6wbWxBXLC09DQXbDDXYdmQAMNRItev/cqbQ0elgIH3m/DSKR3csNGADyjd8/db6s2ID6kp//61stwyf6l9ANgDsBJjWoZhmy0YPMrsBx0ZAzUl/C7INgE1WGlLVr2wD4NsDeAj6p7UKVtWcP/Ys0p8onX7Fz9UtMvranR+G29QLJ79qWdZzPOydfgPf++72i27SeZo+WyBc/T43Kv3pARkAcfVgW4a+/OBKLwBV71pZWBKvogiABSHQZ6Zq2n30VYYGCGgCQPlVtVW/jme2XsVwKDxIz08CaE8cEkfsNqDTvWzXz8AvRxtAPic5MvLa6+VhGi20AeV7c1daJPqXn95P9A2W1mva3b9yphu+Rwg7X9fW2OfSufhPkjflI2QDxHFLeYCcBeRtA+gliw+fhLp7S/lsIFrzNqgYME29o6vmF7sh6e+WxG/P//GW/nbcbID9zHO5I6ZRJx5CpOcnL77i682wtXirf8d+VvIvp3cy1WZ0AWpU+jviaAO4BRDTEBwBYDZES6Q/4V0crA5cFB7AfyjAe79fCPrOrHm/Y03X0JN3/ufYpb9P3S+ou5suFPCWZfO3MBTQ6F3JZ2tO+tuvHoql958tp9y07/vJ8lwxv3Y6EIVR6jKKCbcTisFeHoUBAPR87i//6pM3ny/n+r96JgTf48OMfPTi8Sgq+/1EWgo1vH5233u3n9DjW0vVUICH9Cf8DPyyRAPcco28+6M3gWM0oLrfX763ciKNxQZ4jA+ri5/GPoszYy+f1IBBjzkAhFuKkVif08OBPftM01xenOnuGzRMQ6kOnjDN2hkUQv3fvJ050uX1rxCC3s+2faPqv6HTdgEAbk8VPGwA/TJvvfr3v/FvwU+oasdKf4LzgpiNwwaAaZIWSn8Zjz6h6sBFVEIBnVkTtaEAOXsHFen/JLgCwCgBwAGzurEnC/rJ+KphAoCm40lgBcC+UlwEATYu/WUclbSjAvbW3NuexrPBU/lfJnCT/gBCsTQ9eHw7ByAQVk8FT17HuPgIz2cuuXkAMdgLFUFvsQF6Ppd2Ec11bYClzJcy/n/87odu64lbSx2BUFSUB9Ql0Xe+biggNTNqb7pq9r317v3Cm8ekZZtmAyzSv/beWmwD/DT2mVw5glsrl84NXru1Yl9jwWIDSP3n9OqfrWkagLk4Mwooib5BGDodNM3y75J9HNiD9F4AR7qsQ+Ic1bybXm9C+jd32rMnQnCxAW5/HZtNExv/FuiXc8va/7dQ/QvYBjAbgQ0A0xibpPtlNhgKUDWFdL+FeWUFwOBq9f4n46sAzGiHApjZZQCaDoBsgCKvJDYi/WUODERwBwDu5UfkYcCOK7dMuze3fy+T6RgFcAD1v0uk5i0Z/N6LHYntWS7lrR+rXUEAuHBkAMD1B+MAwp3XAER75nILX3I8z9iTvYP7ntoF/eKnn9T9t9CrLNg7/BDv3X5y6WQcwLV7zrozECq/kMIFPm2An1CATHJK0YKRUDRglArX5k3DKL7WW9UQLbcBHz1YT/S1WfS9hdTM2ItHIrDN996gDejYd1wccdzvF6O+6p4w0Tf44T29mM/K0h9ATyK2kMpVvjLpp9B14BQ99dJJzWNugMUG+E/i36D0dzut95ktNuDZlf4ep3pWpL+MKA9gmIZgA8A0xqTZ068sbMGFPIqD3UIBC+FVjxMGDRPA3djK6WxcSH/xrBLrIA8AQNOhKiatpCOtkv6CQEihob912YEZQfZTkfT3g6zmA2GllDc9ruu5659xPE7qXyDbAADRnncAONoAMa/31TOhq3cKA50P3r3pfAkZu9pwk/4CSvK5dDJu8QBC+stshg3467vFQKhNgQJFhaIChqoG35sJv95X891urQ1w2+YXUE2w20WbtgE0wwvucwCIujbgw3vldv6zn04l+s6bZk13/55END0v320+NTP65YtxCh3UHR/2IL03GI6SvK5LdyM/kfTcpF7M+3mJ/9OePRFKz03eni4AvmoDWkjTOT8+T/Usqn/BmOkaZGMYR9gAMA0zafYA2AIb4N0n1BIKADA27TxAl6S/4G5sRYk6NG5XYh2KbgobsDhVeA+LF9+y1uluEFnUzt/OzcOXfN+B/T1pzZ3ZD+quJDzUvP26TUh/D8gGCLxtgBaOfmUodPnjDOB1IUepUVf9E7eWOgBcOglUQgGO6l/QQhvwl9dnI+17TVM3DEVVFNMomaYJ0wSQvJMdOmPdStwCG0DS389FjWLYvweQ9/vfHorT5r33S8gG4Nzz8kEh/au3VymrkG1AMKACWM9lAfQk2ujq126tiJJiNxsQrPSKfe/yrdffqFNN3hCizph29xtyDnVPK0YO+ywR3jit2vh3O0/L1T9Lf2aHwwaAaZKdFgoAoOl4PF71AMHKp7P8Nky7/h7N7ZRYx+J0XsmumDG/Sdg+kUXtpYFfuHr7h/TY5xb+Tsvmv3Ll3f0D0VBMBVBwL59FPelvua7cGsiCRfp3nyhnYlDqf11omSgUjva8Y/EAWjharpEdOAcA8WMAsHLfcp6NSH8ZsgFffrMfFXH/vkteEPHjdz/88pt+m9662QDTNA2jqJS0rkMnVS2oKIppGosPPjH0Itw7wjnM8NoAlO3zkZP0r3tRn6EAeb8/p4dJxAfDMQAeNoBelZoZE/OD7epf+leMAjh6ulxd3R5VALRH27wLi+O1H7lC/bc2ncaxxdDGbYD9tFtjAzY15+dZh9U/0zRsAJjG+E9/9G/+V7/yj+jxzgkFoGIDNB0LY+uqAnsoQE74cWOxIlVbq/7rKuDtyubfYGOfx+O5/QNRAKGY6ugB/Ev/usjqX0h/gjS9fxsge4BIT3p94e2q9Lcj2YBWSX8iEIqm5yd//O4jIevdbEDT6tBuAwy9GO85pgXDhl6CCSgKTLPr4BlDLz6eeA9ocztVq0IBQvR7q3/vi3rYAIv0ty9wswHyCy95Sn9Be1ShhkKJvsGfzDjXGDgSUBEIRXUT2BLpL9OcDfA+7dnjoa6D/cBKcd3X26Z/P7nZOT/PNBbp/70//FfbdSfMMwobAGaj7IRQAMgGzP5QPCtCAf0r7ZTBf2/xusfJF6fzx7pejncDwJTnSv94yN9T88bcolUxN2QDtj0U8Nprb1658u7j8RwAORRwZ/aDM72vbI30lyFZn5+sbwPkUMCbL3T95V/+dXHpjPdLlM4TgVDUMht4I9If7srv4sm48AAtUYdkAzLzk50H+uM9RqmQM2GqesnUglAU0zRgmkap0LHvWOLIYe/eiBuxAX4Uv52p3IGpO4s0H8CCow34tDBA4t5R/QuC4dhLJzXHOQAiYuAB7feL1167tfL20PP2EQRuvDrYeX2isPp406W/2yzhhmxAXVMh6oaDkRUAHjZAqHA/v0i88e8Bb/wzG4cNANMCdkgoQInFAZjZFQAnV9rwPkqnL5Yqz57svmD3AKT7AcS7qgdPdF/YoAfwlv70oE1V1wzD4mqwUzOC6oYCULEB8aXBVql/n9JfJtwf1Wd8XV30DH11IPzzG67LFFUNhMrxgY4Tp1GZ6uW/TacF2vj3XnPxZDwzP+nWKag5aKrAf/Hm6T+/ct8wSqoWVLUgoMA0TNPQS/mvvnIY/lqkN2EDmlD/Hp1DZWQbQMJ93aBKBi8R/9JJDQCpdnhGDCxYpL947Yf3dGAgGPZKMZIpFXIXToWuTxQCCgCUNjaQs7mJwnVtgH/pL+NmA+wq3O0XiTf+PWDpz7QKNgBMy9jKUADc+4Qe7x0CUDoI+7Mnuy+gEgoob/l3OV/iRPcFNBUKcNO+9oKwCye+kjVM+z/H/i/yYAsygvw394zOn7Nk8N+cPqkFw4OHb9kXy9MP7NdtQvoDWJzKw9YIyA+OHf1l6V+lMtD3/XsrTXiAc3uWgeVrPlbeWuqQq4RbiWmaeqlUKqI8s8oEFEtbm9bagC9+7kLds1nwqf4FNyZNAKvS75GiaAAs/y5UpL/g0wIViFube9qhFzqm+uT0sPilq1tpIBhf3NuWwED3U2EDmqA56S/jaAOak/4yZAMAFNfjbio8EFkBsPzkSmk9Ln6RNrvYd2vYpApgVv9MC1FM98IvhnFE1AC4sTU2ALWiuS5+OszY8T+n1r/0B3ApXk4jSWZqExhq/0X+p2V5Z/M3dypLc88zvVYPcOXKu/TgWNcFeiAMwK25F6PxfVooqmpB09SNYuFo9Pv0lNu3lK4bq8zBRePSn3AzAPaJAQACYRVAce20OHL1TuErQ+eujhdI+lfngplK33GHTKGGbMB7t5/QoF9Z1juW9orZwPJ6/0XA3vzZu5NQxG+aaZrG114/6bbYj3D3Hw3wONtU7sArZ7o/+nTd3irUMQWI+OjTdQCr6156Kx4FbNJf5PmsVLLGhFvoiFlLWuXXyqk+wjbYXwKgmM+KLkAWro7VVLSTDfji58/Bs2GojB/p33Ww33vcrwWyARtX/wJxqpIUEFA05w+I0npcC7r+yW92zk9ruwC13ADUlf5cA8A0ChsApmHqGgBsoQdAIzbAo8OMnc2W/jLCBgRj6cmodWbt1tuA6fQNe1GvowEQ0p+g7/DHUyfbEn3BcLsWiqha0DQM0zSK6ysXz494XDTYlnl8O0eKvDnpT2zQAMiUZwNXpkE7GgDCpw3wL+vFSnk9pfG0imQy+eZbb/lc3EIbYD8V7ffnjFA8Vv3hyTbA0QCQ9Ien+vcp/WVMU5fVvNtrl7M1sQVHA2B5rYzFAAAIhKIXTlXfHLxtwM3bGfsUYRmLRvdpA2ZzR0zD8DhzQwPI3IyEW2UCqf+SUwnBFmz872QD4Gfjnw0A0yhsAJhm8OMBsCNDAX48wFZKf0Eolh6RogEPutVCtkte0CobUPc80+lyRrzFA9gNgP1C9O395NOz4XhPIBgJhGKKFoBpmqahF9fXlh4Nfd7hUzbYVhVDcpceb+zSn7AbANlOWJoFeRsAoxBFRaav5HQPA0DUtQH+Zb1lJdUNr81cBzA0NGRZnEwm7Qfr0pABgO8cnoZsgJD+dFA2AATZAIsB8CP92yMqAEUxHBW8o/Qv30Plt88u3/0HDTykPyEbAMsUCD824Obt8svtYt1Do3vYgNlcOaZhGobjmf1L/6s/mz/T7zWT0dsAEMIGbE2xbwvV/9ZLf7D6Z5qCawCYTWS7qgKaZjOkv7fuBxCKpekBlQXT4yOLBpCSbcCWTfy1N/bxuBBsNiD5N7nO3lwgn4VpAIqiBUxDNw1dL+VN3SpnZOlPgj4QVi0N++24SX879kiCz56hJP2JSyfjAK7dW5H78zjS0MQuAHfX9gO46LmG1OFSOg0A8ZMAkskknGxAQ3wwnSt1nv5wahXASyfa/bzET2EAfNcGPDBPAsgZRe9lgUjbi0drflfr5vyQ9AdALzSKNSXCHtIfLhEDuAcNHCsN6qp/geMAuOsTBVRsgJ8pwpDEurdMpwwfuw0Q6t/tzA3l/GTm5tHvKlvpVHUjElQe0HWwv1gnqFlmhxT7bov6Z5jmYAPAbC5b1iAItj6hDbG90v/airMMOrJoTEoKYStHfck9/tGIDSgV1/XCejGYM00TUBU1YJqGaZT04npxvbovaJf+1htwCgVsRPrLeNgAWfrLUKKOn4ldfuqDSfmtFtAecrUNFnW4p6ur/KjrwtrM9eZ2/QF8MG39V2+SDXDzAPL+vaJqAEzDuWNPo9IfFfVveSGVCCsKPv3/t/fnYXKU97k3fld198z0LJrRAhKLVgRICIQEBgzYMMIYJC9YxHawTSy8EC9xnJMcX8ec11l+J3Y2TnJyJeeNTS4fEgdOXuzEJgjbMYuBaYPZQWhFEoyENqQRaJnRaPbuqt8fT88zNVXV1dXdtTzVfX8uX8lMT03VM6Nh5r6/6xvbxVBUJ6UC/971QgIZ/vcv/VFu/XOlNiDTnF2+pMwvHIHVBrhKfytHRhYA6PJzX6D/SO/zvzqQ0t2PYXURpayI82L/o0XjhdKfJA4aABIFKqcC1JT+khhnBMlUANzqf5zPEg8qTIyNDfVDSxUyY4VCXtfTplkwC4X8xMjo6RPwIf2nDmBJBQQl/a2I+h9JKenvLNEpawM8UgFS+gtOjRQAzMimbLbBWx22zb/8ZH9/pR7AKf2tBG4DXFMBriLe1QZYRXzV0l+aDQCmqQOaWItmtQG1SH+PeiFvxCqAspf5sQFynfDOveMAfNqAd43i+COPa+Sdn3/u9auvucjjyur6hl1tQI2jRaMn+n5fQgKBBoBERMSpAJSzAf51P2KS/laqXheAmiuCxoeNsupfPgjA7V9d+O8/OGkU8qmm1nTTkJ5Km0bBMAr5saGhEwcybcVds/4FvewMLkvVrcP+pb+VKiqCbOpfImyA9fqyHmNmV9dJnPf4qwdvuny+xxkErtLfbNb6Rwe6WjqtL4ZhA8RlZUW8sAFwk/7en2ir+XF+ru052ZnnChuw8IKiDfBf82OlVL2QT4Ss92kDZGNAx/Q/2lKjS/zYgF37CpOfPm1oqWwAsN627NoKp/p//lf7r75+oXi7bPmQ1QZ4X2y1ASpIfzDwT5IMDQCJFGEDENXWMFcPUHvIHxFKf0nYqQDnrWYuqMAjWTGMQn58eGL0NDRN19OmUTBNwzSNO/5rGyqR/v6pXvqPtQDItO6eGJ7W4Otz3o7PiiB5paaLX7nuxRweNmBmV5doA5gqBBIeoL//8VcPit6AUngE/jXdvSf+tb2nfXoAeNoA0eN7oLb4fRXSHyXUf+ucRQDMQj47c35K144f3HHZealZ86flKEIN/DspawOKmyjOnxaAT+tIN2ULpUd4lLIBUvpbsdqAWqT/8786YLvAf/NAKtNcqjnYRqZlsP9IL1DlJr6goPQnSYcGgMSDdAJOAvQGTtGcH/M19kop6W8lmoqgqqW/4FNfnP3D//OunkqbhmkW8iZMAJ/9vbRS0h+T6t9JpdM2fdqASfWPjpY0gMHRSm2Ay8XSD7gWHXnX/HhTUSoADhtgHe+jhSD9S32iRKz4leLeeqvUpO1pn7XwzX5DGxwU0/ojlv5WXG2AfQmdBVFBlNIAwKcNcJX+VjLNrcsWpcSnVBH1t5LSm6sbGOp/ObHoEnadGRoBVP+kDuAYUFIlPieBVk2wKQJnKqCUYo5X+sspQDYmpo8ERSVfkRMPD2Bb/iXwWQJkw3+tvxUh6F2HdTrJjxnORmHnGFA/0l9kAGoftO9hA6QBsDIwVPI7MyNblJhWWe9tM+TFZaX/yZF+PfNmukUbG1hkqwJy4t8GAHhl93FYJnsWoKdL5BlCkv6Cp35dXOOtzViQaS4Wnk2MDQEwCwWZOihaFF3vbEsjDunv5NU3x53SX+wIc71YvOFhAwSywsqVZYumPtp/pHfnW/aMhLUHwFX9y/D/rHMuAnDV+32JWuutbBkA/8uJa7cB/seAKij9OQOUVAcNAKmSsA0AQigT8t6zG+BQf1QV9b+yIwOgZ8BLK9ucQLA24I3DL4uWXxuVGoBapL/E6gE8DIB4w2oDrAbAf9S/dcaHfZ6zLKU0uqsBMI08JqP+rggb4OEBnKVBrg+y8p7F2SfffBpAukXLjxrXnfd+Ee/3xo8NkPLdNAoFFP/VnAbAtXTHf7m/t/QXCAOgzShOuelo1tMtbScHBjuadcMowGJRDFNLpTQAeunvW2TqH5OBf1s2oJQBEJS1AR7q3yb9rR+y2gBhADxUuDAAQv0DKBTGr+n2GjHkvJVrCZDP5cSozQb4NAAKqn/QAJBqoQEgVRKBARBEkApQRPpbKWUDVu3ZM/Oyix4/Mk2mexsbb6w24I3DL4s3bDbAvwEIRPpbETagrAHApAeQ6t+/9JdPHzl2o88D+8FpA5y6/D2Ls/JKDw8AHzZAcnochmF0trr/lIonAnjyzafNwvmmUWjqeEt4AEyW/bjdUzONfEdLCqVtgDVyX5j8ZxHVXzYD4BTxtXT6uvLUr1+V0h9AR7OOyU3D+dGhoXxR8hpm8WAeBiB66W9FKntvA2C72GkDShkAqf49FLawAcsXl/m99/ruZgCpVPG/QG8D4FP9C6wLwspShQ3wo/7VlP4CGgBSHTQApEoiMwAIORXguhs4RulvxWoDVu0p1oDPvOwisR0sZ/loIKkAaQBQuQcIXPpbKXVDqwEQ0t91ZmhZ6W8lPBtgNQBSiNuuLGUDBvp65R7iUjZADhcyJgvJrDZAPvHpg8+MDS4FoOnFyZupjNY6a9/lM68WF1htwOnx4n8dIlMBwGkDXKW/ldTkz2bgnb6ubN4/enKg+G3paLaV+qQAGEa+MF0juxqAeKW/lVffHPdjAOTF4g3rl+g0AB6BfycH+s9wrhyWdJ219LncQfF2WQNQ6llBGQBBRTagrAFQWf2DBoBUCw0AqZIoDYAgvFSA1QMoIv0lPQNjUvoLZl52EQCnB0DNNsBqAATSBngYgFClv/c9hQGwFf1b0wUVSX8rYdgAYQCc0t95pdUGSGkoDYDAagN6dk7LBhjTO0k6W5vkQ195a2RgYkDXAQ2FCdM0CqmMBsA00aF3SFn/2t7TUvoLpAEQCBugpdJwifrDKORTqaKYFupfiHizkC/lHErhs+ZHjC2SmQRR6iPedu1GmMjnIb5sccjpBkBajsuWuncvBIu3+kdVrSk2G2A1ABVJf9HLu3Vn8b9xpw2wNvs+lzsoDYCzB8D7WcEaAIFPG+BhABSX/gIaAFIdNACkSqI3AAgtFSAMQBXSX+p+hCD9AWDrTvH/T+an/ju1GgCBtAGuY08rqgh6+qlnrO92LJlobZqBEgYgRukvyI8ZzpZfYQCqlv5WArQBftYDWy8GcPCt3dYX22fOdV6p6ykAXV0zYRkrZDUAMya1rLAfJ4f79bSm6YAGTYNpFIplOqZpFNDZNAOTsh7AoMWH2AxA8eky3GsAgPwZNQp5AJqGTDotxbS4YXuTienOoRQ+pb8Q/WYhLxxLx2TndH50yCr9xRu2YiRpA6wGwJlw0DPBT68SlJX+qK0xXdoAQyt+W/zU/Aisyl4aAIGwAc45P7968s2Uln7fDYudd/N+nLhVqcXAVRsAQVkb4GoAErTeiwaAVAcNAKmeWDwAQrABrY4mRf8hf4Qk/YGeZzYDWNM59cdP2gBZBWQlNzDmsfvMpw144YVnx4cNAB1Lil+UqwGIXfoLXA2AjtYan24l2FSATwb6el+arO0RKjyfz3edcY6101eg6en+/pOY9AAABkfzwgDMaNFtVwI4MXxST2marmkaMGkAANM0YRTMruZOWAyA9QClDIBN+guMwoSmaSL2r+vp9hZdaH3TNPP5PIBUSisYyKTdm2591vxYOwdsf8g0rfhfdN6Y9rrrPCJj8kubMVkx5frcYG1A2NLfyqtvjut6avV5KblFuNLFvTYDACDTnHUuGXA1AJU+y2kDajQAklJOwGkAEhH4F1D9k6rhHgCSPHrNOeHtEQtpqH9F0t9Kz8CY9AAz05o1FWCju7P5PpQ8kv91AZ1LJwCUmEeqivSX9+zKTJsXZIxn9RL/gEd3jc6tJBkiyM55AtHagOd3vgPMuPI8AHhpz2BHNiUkuFP9C7q6ZgoPIOhoSbuKdYFpwNQBA9ChmTAn9bFpwDQA0e9rjsOihkVMvX/INI1CyuIpDKRMwy79BZqeglEomKm0rpmm2T9cSOtaYfJiE8gXTEwG4K02oKz0t5X6uOYQCiZgmqYJXdM0aJjsRXYy+bimVQtbROeDh+UwJpoRkA0Io+bHA+sW4YG+3lOev7fKzu+Xm8J27h3v7+u1jgd14ifwb8O6GBjBqX/4Wx2QoMA/ITVCA0ASidgjFqwNUE36r3n/KpEEEK3AwgbMTLsXJT92cQrAPKTgb9WXk7f6N43mBzuXYnwYAHQdmG4Dwpb+/m9ru+fc5VnhAYxxr/J6AEd3jQJQ3AZcvfzM53e+8/rJGQCkDejvPxXM3U2YBRM6YMLUNCH6TRMwTQ3t1rr/U8PjwgMIkZ3SNRMoGEjpMCDKSLTS6WMNegqyMUBD3jA1aOZ0JS7C9tIGeNf8FBsGxrVndg3BEuO3ItteRT7AMPKiqsfVBtge53PXQY02IFjpP9DXW5gYs20yLvvoGRkAcLUB3uq/liXBFT0IDhsQIDYbYA3/JyjwT0jt0ACQBBNUKkA16e9KMRWwcrntdSH9rXhv/HWmAt7q3wRg//Z3hTJuak0BGB8uYNIGaKm8Vf1v7339LP28sgeOQPpL5i7PGmMtR0s7HyvVpQIQRzbg9ZMzLpp56srzOoCO13a9CmC84zxMZgNO9vdbewAwvcPYdU7o7I6Zx0+fhGEW8Iae1rQUTAMwVgJIp+x/DvqHCwC6Wos/YGbB7B82CgZMFGS/rFHI645P1IDjB1+fNX+FUNyakN4l+mlN0zzV1zvrnPNXLZzheoEt3l9U+ea0AaM26S+Oa7uPvLjSsUJOqrABgdf8yBueOLijrAdwPt1mA/wH/mFR/67h/0prfjwIMPxvQ9gALXVEvMvAP2lAaABIsgkkFSCaaLs7Xf7YqCD9i6xc3gPAUhHklP5W5i1r8U4FABiZ97r1RasybmpNjQ8XoJnNHQZgby04YuwBUMoGRCn9rYjD+7lh1akAANk5T0TsAdJN2SvO6+ietxRALpcDcBLF77yr9BeInmOnDbj5krN/sbkHgJE3UykxWWhkVnvX4PQJpEZxNE6xB6AjmxocM1IpFAzA1MQuLT2V1vSUCOQ7Q/JSmE4qdtPRLABtUpt2NOuiCMc5JgiWUh/bhHtR4l8M8JeW/rY5pKhB+lvxaQPCk/6SEwd3AHC1Ad5Pn5FB57ylgyVLxoqsXN65c+84/AT++97E8iWlPupf+sPf8q8a8VMUVCmU/iQpsAmYVE9cTcCuBJIKsHoAFaS/KAFyRv0PzNZnLfD7Z8bVBhyf9QImG3wF+7dPDfibu6xF1nesXLDa+enbe6ecg9UGRC/9ZROwGPvjNTN03P13XXU2AGGmAp7f+Y54I900Tdbb5gi9vGfQz2hReaX1sse2HpZvz+rokm8PjhTePbD9jAUX2+6gaZqo1bH9xZDzJYX+l8U21uINizA1zUJBXie0aUrHuYumTTgFIAv9p6R/sdvY/R9Rg2aYplP6ywaDYKW/jW1vP57OiL0KWHHO9dYPBV7zY3vFOT3TagMqerq3DRBy3LobGNMzAP1Hep9+8g1dT79vjbsB8K/+I5D+sBT/iPB/IDYgevXPJmBSNcwAkDohwFTATWcVm0pViPqX+ohHNb8NWypgYMZ2eJfBaObR3SMAFq2cdf48uzJzcsTYc5Z+XlxR/0rv6STAxoBdY/9SyJsAVrR93nbxvz/+ym/e5HehMhzSXyDC+dIG+J8rarvylbdGRC2QpmNma5f1Qx3Z1AlNs0WUCyY00y79JdbQvwlTc9T6nDi4AzBnzV8h9o4BGDjSq2lIlZhZNThmPL3zFCbncrouF3OSSWkT0yVsSIF/GzvfebylFakUNA0m8Ma7vxrsx+XnXx9B4N8V8W9XtnjG+eiONFDCBkhFLvYB22wAaq7493+r8KgxG8DAP0kcNACken784HeVSgKg5q6ATGs/gJ4BtOkl52k6CUX6A5hs/O0ZcJe2/gf7iGt2H37F+uLRXaOtTZlpG38no/7Zpuz5cy/EScDHH7VMVt+9d9c1Sy4tf2m40r8mbVdjY8Brbx+yvrhj6AdOD+AfV/UvsdmAinjlrZHyF01y4uCOgglrGY8NTU85e3EdHqD4qcf3bwGQzrRg0jOIlmIrg2PTxL5P6a9P9iSIeP9EPh+N9Aew9eDjU/9WGmBC0zFx+s2BvnO8PzEM6e8T70fbbICrHLfaAOsFup42jGneIBHS30p1NiAu9c/wP6kFGgBSb1SXCshY5vr7JDzdb2NNZ7PNAyw4bvROyg4/NkC0+Ta16gDEmH/J0V0jc5dltVReqP+i9Jcf3TkCYO5ydz2ayer+4+4hSf+Cj38E6z09GoWrSwVseWcbAD0DY2Km9fUdQz+AJRXQ1Dbr33/50m9+8Eo/97zivA7XFl4rFW0Wgz/pL1TyiYMpAIMjBVFwP5kNuFhPpcWGL0zfLOskpQuJP1lhauQx2QNsVfwFY0ri26S/4MTB7eLR8hVtsqNYoMNe89PeogNNAMzJo4Yk/QH8etvjHZ2YzGpMJklMDJs3vnwQV8x3L6mJUfr7f7qwAQcPej396msu2rpzYEFX8V1R/3PdB5bJC1Sr+fGPfxvAwD9JLjQApD7xbwNUlv4SZyqgqbXfugvMuyJIqPzJT9StHkBL5d95cxAO6T/t0x02QAXpX9095y4rMyzIvw0Q0l+iZ04CKOS7rC8KG7Dj2Uua2mY1tc7xc2ZBqRZeKz5TAf6lv+T0qKFpmrVF7MTB7cIDeLeNpSZD/2ldAzSxY0uK9NT0PVwpvWgA+ocNAKkSnsJqA1I6hJUwHLsOwg72OzFNFArQ80VHohkwzeL/AOx690zo5rLZ71o/JVj13zlvqbBnfvA/MFQ+2s/A0AP9Z2ByN7Dzo36IV/17zP8pawOo/kmioQEg9Yx3RZCH9B8yDNcqoOilvxWrDVhw3JgYNqyrf71TAUd3jQAQNqCpVdd1zTANLZUHcP7cC48171uxZDkwbamW/Q47R4QHOL53bA4WH8eusgeOcVOYxw2FuK/FBtikv5WUsAHTswES/0kAQY02wGfBj1Uxb94/enrUKEwuCBOCvf2Mqd2umqZpgGGasutXhOSl9G9vMrVUanxyxxaAU8Pj7c366VF7tB6TCYF0OgUgny/A0wakdE1IWBnmPzVcLDiJXv0DyOeRn4CmIWXCNIpNwMIAFL9/hrbr+BkAls1+N3DpL94Q3xCfNsBjWJDHo/0MDD3Qf8bMJW0D+7aVusAV1QL/rrjaAEp/UgfQAJA6xzUVkIiofymsFUELjxsAbDbAOxUAYN6KDDRT1zQAMxc0H8M+ADv27lyxZLlcquX+6TtH0s3FZ114zjIAu992twFqSn8rPm2A0wNseWfb6fHTRsGckS0ZGvS2AZVSnQ3wo/5NvLFq4XXibTl1R6p/TJf+Jw5u1yYj8ZlUscRH09DeUiwZam+a+kQpTFctaBHtGZveOg1gxOECpJb1sAEydTD+7k4AmJSwM1qbIij1KUUhj7ExmCZShckmYJEBMKaNI0o3ZXsHF2BwXG7k9aC61uGgbIDH0/0MDJ194VVHRrJdfg4Rt/q37v/yg9UGUP2T+oAGgDQEMhWQaOkvEamAx4eL7y48XkwFiAk/81By2owI+R/dlc82ZWcuKLlUC56pACsXnrPM5gHUl/5WytoAaypASH/5oVMjgwC8bYDTA1TdH+zfBmh6+V/s71mc/cXmF4Swto3bnzX/4hMHt1ulPwBtsrF34O0dABacf4n1o1J8i1n+Uy8uvBzAiQM7AFy2uB3AlkMTMhXgGhQXNsA08qKNIOXY3oVJCXvD+y4v+2WGyo1X3tSz6XGjgFQKenrSABgwCuhqnyWukf3cA329ON9lbZaVGmeG1mIDfD661KSgTHM23Vy0fzv3ji9f4mV1Yg/8V6r+Jbub2wCkMRjs6gBCYoF7AEitqDYIyJWm1uIi2/O0d72vlLTpuoLS38r4cFduMhXwxvwdAEbTGoALz7YbgBdeeFZIfwDnz73wSHYngLaWNltDsKgCsuK0ATIDYGP2kuYwpL9ArB1w3Tsm9gDMXtIs9gBUTSkPcKBlN4CmVt0q/QEYlpVU0gNcemZRFr92eKv86NbcdQCa2oqKcHz42IprdsBtVKhPyvYHexsAuQ3gF5t7UhltVuuVkEt2i7P2i0yMDhVvqAHA8LF9mC7EZ81f4Rp337x/1Pm6sAFiPOXekXmDloog24FFJkFLpQ+8uc32RMmqBS0AZi3wW9QeEk++8ri1VNA0oWmYKCyc2TGrKP11E5Py+ob3lzQAYa8LgNvGAIn3zNBSj352W/GXqlgS3H9yGNAw9jZKbAgWqBP4r2j7r2vUP14bwBFApEaYASB1jpT+gj3mGT49wJAR8HL4MOjubP73mZv7J2eptORN4QGsZNoGrLX+m994DZMhbde5QFa8K4IkQtCLhQB+rqwO1/vXckMrzlSAkP6j+rCBwvi419CbUyOD7Zn21WevlK+It602wIltTJB//KQCXLHtC0ulLtSmS39MH/eZaWnTgImxIedUTcECbQ/gIsFdXYFVrK+ezBUMTm8MsBYRuT4Rk9JfIExFjDbgA++5CcCTrzwuv3E3XHGTNQ1SVtnHtS7AJx6PTutIN2Wtu5kH+no7Z5acYKtU4L929Y9wFgkTEhnMAJBaUTYDYJP+NnzagDWdwejLMPjX5n3Wd6UNmH3abL/oSgCZtqnvwI69O+Xbh944CWDJqtnyFeEBnBkAibQBtgyAVX97xOlRm1K3Lh62PuK8C6fuWWMGwMrRXaMHWnaP6sMAjuwamrusJe2YeikzAO2ZduvrVhsguO+BLrhlACS1bAyw2YDT4zAKhc42l2+1Vf2/8taIdqr/eCoLDbqZKs7snH69dWrnxNhQR7N+6t198qNChe8dmQfgPRfOhj8GjvQWJsasel1o5dPjmlP6n3p3ny1obZX+TmLPBlh5be/p/r5eAJo+9XW5ZgBe3DEAwDYsSBKg9C+VASgV/vfz6FffLDZhHz/SO3BiGJomDIAtAxC79Idj769P/Jf7R28DmAEgNcIMAKlDvKW/wGcqQLTbqmYDHmjtBYDCtP9+u1J6aqAYT7VK/zf7ikUszg0AsMwF8n6iTAXkxwzhAUoJ+iPGHky3AUEF6a2PaG3VL1s4NXE8QPW/5Z1tp9tPA8Dkd+vortG0nnJ2A9ukv0BE/aUNEOrfxo7nVlg9QNWpAEzPBpyeXME0MDwOoLO1WIdtk/4ATg+NIdUKmEAKYly/ZaGXfEuo//YWHS1T4kaqcKH+fTJgkYDWsP3qJVPfQxk4F9JZT039eHtLf+dtYyc/PnLZ4vZNb502DQ3TbYArcliQ9cW4Av/+n3v5+U0Dfb2vvjnuyDtOoYL6l4Sk/sFsAEkgNACkrvAj/SV7zDPgLxXQMzAWuwcQxe7fy1j2bqbyxqQHmD1kAkBa1/R8f95l1Rc8F4GdP899A4AV2RzsR9ALG3Dx0jJdj1WQyeoZDQA27d9l9QC1Y+vx1XVYq8Cs3cDtTe1G3kvSvXZ4qzMVYMXZH1yLDdD09OCovTFzYHh8Rosu5wLJoUCDQ2MakIeuA6bcqjXpAayBf9tszRNardLfilOvr17SPnCkVwwLsuJH/XvcNi7eGOhsn9V5QeeAtAFl2XX8DOEBQpoZCh8twlU8Wkw3enXyRflfhjrSv9Ku36rn/NAGkARBA0DqhIqkvxX1UwFC+n+/qRdA2vL3FYCeys88VaxO0fSiBOy63K5+XJYATI56PH/uhceG9/k/TKmtwDaKm8Iq0BK+7pmZrqM27d8FYNW8VTXe2Sb9JbqOcy5qe/v1IfnK0N7U3GVZ0ezrXeI/+dHrbK83tc4ZHz6GEqNCPWxALpezvpvvvMAwCh3nPGhMzO6a04VjNwKQNmDGpHYXC4OF+h8cLRj5vKlNlTNNGwVjmpqm2cr9rdX8sxas2Lx/ND869d3wppT0t2LV6+J6MSxI2ICKpH+p28aL1QYYE80A9IxXr3zv4AIAl/vTn1W0DntMCqrRdRRtwJvjaQ0d6TJbhFWm9imftAEkEdAAkMRTtfSXKJsKENL/23u3zVs2JbvTWtEDzDptAoBuCf1eWrKIH9P3Aeu6JnqCxRKAAKloSbBPLl560d7D7gsHTEO3Vd1UhFjp5ar+JbI6pr2p7dIzV+IEcCbgr9N3ZffTYgqQlTs+feq1w8W3rTZgVDtqFMxWfZ5zVGgul+vu7hZvCzVvzPwhYAIdeTPb39/fNecJADh2ozm9xuHUqPHkjgEAup4qGBDq3xaOPim2/JoFLZWGm/QXPPXrV2fNX5FuafPjAfyof8mJAztslejCBngMrvF5WyhjA7rmFWWlhw2QM0OfeuZ1j5FBgloGBzltQFA5B2EDBvp6PbYIK0uwA/5pA4ji0ACQWvnxg9+Nqw+4dulvRalUQNf0AaR9u0asHuDMIRPAtJoPT+kvEamAlfNXJUX6Y/JbcdnCZSLeb0PTDdPQ4aPqxoYf6Q+gvak9pY0Wpf/kaKAD+3DFokvFBWVtgPQAQ8cP3PmFvPws66ekMieH8sUS/mGjT3gAOFIBFuk/RSadnkB2cLTQ0ZLKznli+J1u8fqp0WlWoGB5z5z0ANpkBdDAwa2GiUXLV8Nzo5Y1Y1DKBlQk/SPgxIEdFXmAgSO9nb532fpBynrRGbzmmlVw2AB5DYIYHORTzXuvBK7u0TYSZANCWu8Vkg1gBzCpHRoAkkiClf4SFVIBNukP4E+WXPLtvdv6do0AuOjcKXEmGu/aL7dL//7Sf25nLmie0EdOtRzAcMlrquP43rE5WHwc7nH66rB9K0TFv6sNEPhMBfiX/gAuPfOSeeeOwjIVFICzAcDbBqzsfvqFjRdkWlzmBb12eOtQYQiQYfk0gGGjD4DVBjQv27xrbF92zuxR/Q1MrxqayBdNhRip2TbnicFRY+TYjbYznDi4XSzxFehmQTxRhwETLYXhCdOcXNxbRheWsgGqSX9MtivM8n29+BJ8pg7ExSJNUepiq7KX6l9iTDSn062YbBGOTPpXQS1NxorYgFIdwBFs9mU2gCgIDQBJGCFJfytxpQKc0t/K7NMmppfxOKW/B2Lv76E3TvrcAFAR23tfF2N/LjxnGQC5G/i5Z7Zc8/5Lq7ihx7eiFhtQqfQX7/bNenN82BDS3/sptrh+2bNteWebntY60u2DY5NH0iYAwMxgug2YObNrYPwgjKMwAO1dAIWJLnnbTLr4m7ytydT1NDCenfMEAJsNOHFwO4CZ567QzIIJZPPDmmk054dNYALm1SvPKl7mT/5a1/H6lP4isi7uH+zFrtTYrOzxffBzsU36l3ru6iXtIjNQdlIQLF3Crqip/iWK2AAbEah/CW0AUQoaAJIYIpD+VRCIDfCW/phU/4Kju0aOXZG96gK/6l9If8unjy5Z1SbeDtAGWKd/2mxARZT9VghKVQRJnBVBpTp9bbQ3tUvpP2UY0lNTQW1PwXQb4Kcx4LXDW/XpcxM7mtsBlLIBekqDgXQ6AyMNIJ/PA0hl+jVzDgDdnFL/4g0xAHRg2MUGpHTt5IGtmfzQrPkXTwDp/FDexOwTOydMAGdZj1TWBogOXWf5vivWohpxTw9lX9HFrgQyp0jg/D54XC8vlurfQ/pL5MxQRDIwtCKCXSsGlWxAlNLfirABoBMgcUMDQBKAmtLfStUVQT717oLjBoADs/VjV/gawiOQGwAwXeVbhwKJC3bs3emxBcw/NhtQkQfw+a2Q+E8FVCH94TYVFIDreujqbICTjub2gWHLYi9tQngAG+nJeL+JkwCMidltji1amG4DRo7dmNI1AB0tOtAENBmv/dgEOgEAF95wQ6kjuRbQVzScp1Q9vauyr+hiK3IlWUVziuCm5l07j8X3wWei48SBHQvTmLVgRc9zm30ewzosCBXagASpf0nsNiAu9W+FCQESLzQARGnUl/6SSlMBlerd1z/Q6v/Oog3AWi/kXPUlbYCfJQDeXLz0Iuuy3iPGnrP082Yvab5mia/6n0q/FVbEDFAPqf3soefL3sRb+lsp2gC3DzlzDh4VQUbe1N2WJ3U0tQMYHJ+eCkCTy5VZHcClZ17y+KsH+4fR1dXl+qDO1qb3LM6+tOepoZNDLcaFkHvBFn/gxbebb7zyvLLBdWsIPBDpb8Wq7Mte72oDbMH+Ewd3ePcoSyrtWPCZ67De3zrS1A+2maHeA0NR4czQiqhU+j+7NXftyu5KnxKNDbAtAVBB+luhDSBxUWb9JyF++PGD3w38nk2tAwlS/xJhA7zpylQmeb/f1Hvk5mL/aMuE2TJRvlZYcnTXiBD6Al2fJjrPn3vhjJMLKjiKPzJZ/VjzW37C/5V+K6wYYy1yAbBrxf9QYajYX1ua9qZ2W82Pn3TBjOntvJLXDm+1Kf7VZ6/0P5vo0jMvERd3NLULJ1BEm9C0KZXUkdU7svqlZ14ijt00uKfUDd+zOCvk/pXndcycdeC9Fx0V774xNO+NoaIMmrVghZ8hOScO7BDl/j6paJDOrAUr/F8vD7x3ZJ5rqc+JgztOHNyRbmlLt7S53mHgSG+U/cqXLW4XTsAnbwx0WicFSV7cMfX7MN2Utc4MDeCUkwz09VYX+H92a666J87IFJ1AqIgOYNXUvyTdMihLg8rCEUAkEJgBIGqRRNFvwyMVUKnYFcu/BDPT+snJFb/n9FdWtW/bAADg/LlTUf+jO0fge8OXN5nstJjC7rd3iX6AHe++qulaYcy45Oz3iA/VEvWXut+KrerGj/SHpdO3ov7gsmuA4agIegGj3neWJ5FfiC0boGkT7dlm65UCuR/gpT3TBEQx0j91/5UA3hwRVT842X8SQK4nB6B7Tbd3jY2cpeOnIj/YGZqlOGCeB3j9E0/bcWYhrlFF/j1Auin72t7TAFYvaXddGlDRzNCKqO5uj/wqN2MmKsmOuBB7UZAKMBtAooQGgKhCHUh/K7augFqkv2RmWp912uwvVNOzK/IAH7zpaiH3XS6ozQbYpL/ktX0vazo6zmzSNJhtqTdPv3Z+++oq1P/mQ7sBGAXTNHSPmLqo+J/qpgVMc2qTl6AW6W8V32U7fZ3nfP4/Fl79G/ttL9oEvfxCxP07mtqHCkPtkwkB14sFV57XAeCVt0Zs0l8gZhm1nb0bwJE3L5935vlmoeUjN60AcN9Dj3av6YabvncNsc9asMLVA0Qj/QU+S30WaCI9MrVp2Bv5JfhpO67oYvj4/tgHBy1ZJd6WqQDVpL+gdvU/datwbIDi4X9CYoEGgMSPgtLf/0IAD0Qq4NY5lf1tdJX+kHt/ga6UXoUHEHt/d+zduWL58lIeAMDRnSPVeQDXlt+h8UFNB4DBdyc0oOPMjJ7Wdw+8dtWc1f7vLKS/lVKDPoWUB9DR3G71AJKgpL+g7NDPJ559+cZrr/D4LA81D2sqoLl4gFwul3s9Z7tMZgAErur/8adfmrss29Sq9/efHB8yFi3bBGwaOXajmPxzx61r73voUQBWG/DK7uMeZ7NZhSilv6TsVjLZseCnfN/2JQQ7qqhi6e/GFRec+dre02JpgDrqPwwCtAG2BgBCiIQGgMSJgtLfis+FAKUQce6KBgSd3rRz1sXF/ypPtBcD17NO2wtOzr3S1wrP93Wv+nVus5D+1r2/c5dnvT0AqkoF2KZ/nho6lcpoMIt7Z00Np45OtM1Om0Bu7yvdS97jfTen7rdhDbFL6S+xDdasTvrD0R9so9S0n+NvebWCVLSxWFwspL9N6wtyuRwcNsDJ7heOAFh57TmYDQDjw4XsnCeA4r/CHbeuBSBtwOb9o+mWtrJ9tBVt2A2Qp379qnzbtdQnqGbl2kcV+bFGPjcGAFi9pH3gSO+mt05rAbXv1S79raX/1bUCl4JFQYSECg0AiQfFpb+kulSArcTFz4Cg05t22l5x6n5UuPwLwMwFzVbpLxH6PuxUgGkCQv0LHwCcPjbhrMmxIaT/4NgwYALoaHZv5QTw2uGtpydOz8iWLJkVNgDTY+3VTQX1wGoDvKV/LZSS+N3d3cIDlCKXy/WfGj9z9iwAYp/0vGXZptYUgOycJwGMHPuAuFLagBND+a6umT7H6aiALPWpSPqjklFFA0d6A59rJFi9pB1A2ZmhsoRJDhfyszus5N0Ui/qXIigbwPofQmxwChCJmiSO9xE2wA8eY228BwT5GR9Ukfp/s2/3m327ndM/rXhL/KM7RzwcggcXnrPswnOWmaZpGqZpwjSByf+JtwsTpuv8/s2Hdm8+tHtwbHhwbGrt7uCYuwA9PXH69MRpAKdGBk+NlBygIaflANjyzrZnDz3vp+bHv/qXrD575YLRWgeqBksul8vlcp+55Wah/iV9u0b6do3csPgy8W52zpPCCQjuuHXt3Dmz+/tP7t32awAe43RUYNWCFin6X9l93H9SovOspRVVLlV0cSrT7LpPwBUxlch7WJCzgeGyxe2rF3aYhqeZLnW3gNT/I7/KBXKfskQzKYiQhoIZABIMP37wu5/8+Ne8r0mc7rdSNhXgp7HVOxXwk7dODZ2fnev2X2WlgX8r3ut+/aQCUHlFUFcGowOFbFcaMKHB1DRNxPMBmKZZAIBN+3eJZV6YFvV3QXiAjuY2PaUVDAjdb+PUyKAtFWCL+qOGcv+yvLR383lYDmD1WStfO1LZ/i8/yDC/LQ/gUf8jpL/r3W5YdBmAvp0jAOZN/svasgFz58wGsHfbr0UqQEEPYA32W5uVS/UoS0LtWLAq9bLblOFQ9s7VAd69y5ctbu88a6kxYZ8UVPJxgQb+Z8wM8GY+HseiIM4AJcFBA0CiINHS34qrDah0po2rDTh+YkzTtAXHjQOWkZ2oQfo71/2W8gAItCJIfjduufaan7/4fCqtpVt0TTdNFB2AacIoFL2AyAPoKa2U9LcyODbUlm49PVGyIkXkAYQNCKrT1z97sBPAeVi++qyVAAK3AULl26p9PLoCXNW/kP5W+naOzLP8y06mAopb5+bOmX302PH+vfd2d68Rs3QUQap/q/R/z4WzxRseXbmRqX9JKRvgoeyFDSg7tsj6tbgODLU/MeSyn6BmAXlTqQ0QI4ASBIeBkmigASDhUjfS34psDq5lmL1rc/DxE2OYnRXa/bzb7VqtCqw2wLscCDU3Bzu/G0Lrj50u2J5+RlenfHsoP4y8rzKGtnQrgBnZDo+CH1iG9Ecm/a3swU6ZCgjkhja8m30rkv4SWyoAQKb1zYnh8wHcfNEMYAaw+P6NjwA93d1r4mr8tSJWknnPKUK0o4rKinWbDfAj7l/e9e4FnSV/f7p+OaVsQEjS/9qV3VXv/6oRPzYg0SOAaANI2NAAkLCoS+kvOZ4+A0AXApgT6rQB7ZctRw1tuHBocbEI7Px55SvUq0sFlDJCH33v1T997jlN0wCMnTaa23WYmNNZVP9D+fJRf4GQ/hIR43fagPbMVAm1n07fYKW/RKYCZi+JJCIKwFP6A/jMumv7yrVzWG1AOrvvpuWz8iOL5Uc3rF8HQNiA39jwuwGdunrEnCL46FEO27FUtFms0oGkbwx0ArDZgLJOxmoDnNLfGG8GoDcF061+7cruJ1/I5Sdw/eXdgdywIuq+KCjdMkgPQEKCBoAET31Lf6vYrXFOqMCaCnjdnPfWu/mPTH4oqB2958+9ECdx9KRfR+E/FVA2B3LLNdfYXtm0f5cf6d/R3ApMFQs5sdoAq/QHMFQY0sql/ato8/XgyiWrXtq72frKgZbdBw5XNvGzajzK/SVC2fu0ASJdkM6+BcDFBtz/D7GnAuT0Tz/jSsMj8L3CruLeagP85zGMieaBI7160+S749OMR7A2IF5cbYAI/9fBCjCmAkhI0ACQIGkc6S8JZGXYN/69F5id0jMAFhw3Fhw3DsyeKpipzgakJ8tqFp85Ffj3n1XwkwroygAVnmrzod16SutItZWa7YNJ6b/q3OKxn9mzCYCRB4COllbbxe9feI11DP9QobwWDCnwL8m06JDzQM8O6SFFvAP/TnzaACvp7Fu5XO59V31evrJh/TpFKoLK7gILj2ikvxXR7eBzhZ48nk332wjKBkyM13iDAKjvbABtAAkcGgASGD9+8Lt3fv2Gkf6QJU8clI1zB5IKkPz8sQMfuXkBAJsNqNQDrD5nWs1P/0TxPvBtJ0rZgK4M9qX29QNz4bdH2bbYq6PZ3QN0NLdK6S8+RewBGMgPARgcHZ7RWvwTKBW8iLL/+uDzAE4d/oRp5DvP3eh6Bqf0//WmC953WWCFwtOkf1X8ate+65ct8nNlpdLfin8bIHuOf/3iD/Iji7q714h3ZUVQx4UtH7zqvCrOECCuu8DCwyb9J0481pSB2THtH6LzrKXek4hsF3tfYN0U9tre02JvgP8TlqVGG5DOxFP/48qMDDKtb5zKx32OEGibs//7f/dU3Kcg9QMNAAmYbNdhADYb4PpiIvDf5htIKsBGLamAtTeusgn3rkzRA6BCO2GtCJLSvyIefWLzvGX2xwllL22AU/pPu7ilFcDg6PCpkcH2TLuttGbLO9uG+m4DABQADBxa3zV/o/UCp/R/brOwLoVfb7oAQO02INOi1yL9n33rSCqVzrZ3vHjoOExzYmzsfUvPcb2yFulvZd7yrB8PINuOc7lcOvuWtSLo/GtvB5DryQHoXtNd43lqYdWCFmDPiQORVvynhx/rbEPTXKR1GOZjEwW8U7hZqnmPSURWKlL/xT3BS1b5OV6lVGcDnnwhl1ZpQn+m9Q0AM9IAMPdQwub/eNA2Z3/cRyD1Bg0ACYVs12Eh94X0t72YCKqb8FN7KiClNxWMcZkEWHDcQLWpAO8ynqM7R44171uxxFcIf+7ybFcGL76xs9/P1W707RpxegBM2gAP6T/t4pZWAKaB1w5vFR5gyzvb+vZ/GFggLkjpqbyRB9B/cD2ArvkbS0v/adSeClgweuGCs6qc/vlM79vpTEbTdU3XNcA0zXRz8692H7j+wgXWy8pK/1xPj3ije80aP8+tqCJI7CIQduCZA5fL1+X+YMRhA2yrf/2M3q8Oe+D/5GOdnUjrSKeQ0qGZ0HWcN3fPMXOaoK9lIKmL9Pd9vKpJbm+AkP5W6qMoiNKfhAQNAAkLq/S3vai4DahluCcqTwX8/LGDzheF+pfUkgpw7eg91rzP5/EAdGWKury5VR8rvUygLH27RgDYbICU/iin/m28dnirntb69n/Y9npKSwEomIWUlho89PFr3zv1c+gq/SW1pALKLgL76u+03PvP+J3f7XR+6MltvU3ZrGkYpiZalzWYJkwzlZ72+7lsp2+up0fofmkDfOLHBmw2tq9dcQVy+PmOc7q6urTUKACzMCW+pQ2I0gPY1L/kxIEdAXoAV22dTqFgYKIAXYdpYsa8paaJ8Tz0wceMDvs/U3UDSVcvaX9t72lEqP4libMBTvUvmZHBDAMJLQqi+ifhQQNAYkDZVECN0t+K/1TAR26e7+oBbFSaCjDGWgDozaNwpAL8q3/5DZHx++ZWHUCNNkB6AJ+Bf1feOfQRlN4fkNJSIvYvZL2up3zetmobUHYR2J1fcNcgpmEYhYJ4WxML00zTNEyjYPzipa0funKln5ofqf5d3/WDqw3o7u7uOfHrmV1dAH763NLWS78+3t8vPypsgJU7bl0bTSqglPSXBJUKcNXWe3Y/du4cjE3ANNE5b2lKx9g4CiYm8igYJX8qqzjMkmwfgE0VHi8oEmEDPKS/YIcxD5NFQcmyAVT/JFRoAEg8qJYKCFD6S/ynAqQHmMiP3LJusceVflIBQvrLt4UHEJcdObR7aMiXdnd+Q6zCvUYb0LdrZPU5F4pjVyn9S5DKHDd005joEurfG73puA4YBRgTXbYP+awIEikFwyicGjl7zlm/QFWLwAoFI1UoABqg6cVlyYZpmEYhbxqmnxGfTrlfkfq3Fg7ZGgM2G9vl26LXVu84Z3j8VFdXl1gsncocB6b9xN5x69r+I733//DewsRoeGOCfFbY12IDPLT1eB5jeWQmMGPu0rEJpHQYJgwTE3mMjMM+qapa5AHEYuBNb9n3WoSq/iXK2oCy0t9JUmwApT+JABoAEiT3/r9P3fn1G/xfr0IqIAzpb8VnKuAjN89/6D/fTOnl/5P0SAVYpb9EeACps5ta9XFP4e7xDbHV8DSXWy3syupzLtyX2rcP+44c8vvpMlHwyDPnl7omlSnuhW1vakdTHuh3ynqJ3jRtiayecbm4bCrAVlB07MiHpAcAcGXpTk0b+YlxXdf1tJkyDEPXUcwAGIWJid++6UqfN6kRWTskPACAR3e8LD40s6vrZH+/SAIAMAbf7u8/2dX1vmzXSQDjjklO/Ud6AWxYv7YwMRb24rBZC1b4GbZThQ3w1tbjeaQ6l6ZbMTSK/GQVkGFifAKDwwEYANenX7a4XXqAaKS/FdVsQBXqX6K4DSil/jkCiARLNX+/CQmQbNdh126BCOjKhK7+BXvMM0Q2wA8P/XyXn8uEDZAc2YIjW0pebIy1CO0uaGrVm9y0u89viLyVtXzfm7U3rgKw+pwLZy5o3pfaB2BU89V4uurcC8VTfv3Kpb9+5dKOrIu4SmWOC/Xf3tTW3tQmQ+96pl/P9Duvt6r/S88sc/GvN10gnICV5zYvd20nOHbkQ8eOfCjTomda9NcOb7UuKPDAKBjjY2MTY2Pi/8r/jY34+hY5i388rvT+9O41a8Q1T721qak11dQ6VTd10lL5o2eO9/f96viB7QCa2qZ+kPqP9PZPF6Yb1q/bsH7df9z/D/5nYlbKrAUrfCr7Ewd2+DnGwJFeb3ndedbS69Z+7fQI+k+jfwj9QxgYQv8Q+k/j5CDerW0VivfTL1vcftni9ujVv8QYb/ZeLBABmdY3alH/khnpohNQh7Y5+xn7J5Gh2I8/aVQiTgVEo/ttBLsrAJMeYF9Hm3zl6K5RAHOXuZdHC+E++8Ji/N6aCqj0G3LW4AKh4/0jAv/Wo45kdde5QALpLn79yqXW1zuyrSjog+NDmBb1b4NFzVs7ca3RfVfpby3ZFx7AoyLIu40YgKajb/9aAPMWPgpMTSvy4KPXrPr581vz4xPAuKbrMGGaBgAjX2WI0rX+Ryh78X+tFwjRb/MAfaNNAOYtywoPMBNdJ/v7+/tPdnXNPDU0pT4v1ZtnL1iByah/KSJYHOazIgie/cF+hLXs3y2YGJ3AyDg0IKWjYBaTABevrH48a4zKviJizAYEIv2tqJMNoPQnEUMDQFQhmq6AWKS/JNhdAcZYFsCCMePAnGnh/KO7Rkt5AABHd43MXTblASr9hsgCnoo+a9P2l9MaWg2MDxsTpql1FYfhuM4GLSX9rXS2jwI4PW6X/lPnnC7rrT3AzotR2jNIfr3pglKdxHqmHyNpbXpORdoAkQfwtgEfuXrlz5/bYsI0J7uBjUL+qx++1uNTXCkV/rdKfHnNvQ9vA8w7P1byYLLiq6k1NRNd5oI9x450Aejq6rphUXEM6PEDO1IZl5Bwpu2NQv9C+a5cHKaCDXCtCCorvm2je5avuPn17Y+J4p+CAROAieUXT6n/gSO9hYkxn19pUqS/lYhTARVJ//OPVtaeFK8NoPQnsUADQNQivFRAvNLfSqlUwK0fPv+nj7zl8yZC/QsWHDMAWG2Adyrg6K4RAO/rXlXR96Q66b/50G4MnMpo0DVo0LJtKX2oUBg4JS+w9hVYa4rc1X9BhyWQ397U5qrmp87sGMjjcb2fVIANcRKjgK4Z+YHTLr9O+/avlakAlLABYsjPl2pe7OWM7svXS/UEp1LNzmu616z53g//s2uy6H/XC0eWvfestSuueODAs3PO6r9h0WXWXWCuZNreAJDOvgXAerGaNqBS6S+56GL3fzJxw8LEGPwNJE2i+pekM5gYD/0p1al/Mf/HP7HYAKp/Ehc0AEQ5AvcA6kh/SS2pAKv0t+JqA5weIK1h8ZkXdmUw1jsC38uA5y3L7hveV9E5Rdtxvv9UZvpYxKa2lGmayE9TDWcNLpCzjEoG/gu6aw1PWVaftXLLO1t9Xu/TBtjaiAF0tucBOG2AR0VQUDt9PfZ/+dkJIEv/S/HOo0f7ukcA3LDoMgC2fcBWhPS34m0DQu0Phj8b4JrBkPic2S9wlfIeLciJlv4AejY9ls7ghstvNsbDqgiqOvBfqfqXRGYDKP1JvNAAEBUJqhxIQelvxTUVIIOyTkpJfysLjhkeqYDV50xr2/WzUEyOD/I/+tM22dM0YWowTGgwi68Auo5TI8Mzsq3iSPtS+/a9gYlTn3K/o5D+5cp4PKj0eo+KIJv0l3cW13e25wfHTjs9g7MiyM98Tz+Unfjp2iJ878PbJt/YKqqAXBMFQvED2Gxs/8y6azG5KMAp663Sf86S4s+wnCha0gbc/w/hpQLgY0yQh/qvSPqjnJq32YCkS38nYTQGRBP4dyVsG0D1T2KHU4BIwNz7/wY2qqyW6UCRTfipEduAoILh/gfHGMv6Uf+CBccMkQ2QHN01eukZq2zqf+qjnitg+3aNWCcIeY/+3Hxot1X9DxzvN0zTAAzABAzL/1onINT/vtS+fal9x/tuOd53i8sdC7qeOmkL/Feq5qtj9VkrnQOFPE4iL+5obhfZABt5Iy9sQH9/f8/rT5950ZyQTi5Vvmtc39UwOFcI37DoMqH+NxvbrdsA5i3Pzpt0jOnsW0LZu6p/28WYtAFWNqxfl8v1KDImyEqlgX+fgl5MIqo/9S8JakxQpaN+glX/kpAmBVWh/jkDlAQOMwBEaapIBSRC99vwGBDkX/fbsKUCABjjWb3JXeuXTQX42QLmXOklRT9MmICmAcCl75p5E019hVMrm2VHwYmD2wHMuNAy9r7mqH8gTKsImlT/pU5ivdi1Iihv5A/tubEpk5m/5DEAT/S+CuDGpZeHd36P9cCpVBOAVKpZJAFEIZDwALP6iz85VulvxbovTKp/q/S3XYzSqQOlGgMQdOC/vllzmXsKq8ZsQOCjfmokwGwAA/9EHWgASALw3xWQRPUvmMwDvClfqVr6S5xdAR4eACVswNobVz36xGY4toBddYF9IKbtAgBds7tOnxgATB3QNW35UQPAoIkJ0+y/vjXbqttcRLFjUg3pb0VWBPk5ic0GiIqgfD4PHZqOTCoD4ODemwFIGxCsB/AYAyqQ9T8lP3ENnnpr0/hwweMpVllfSvqXul7NxgBK/2CpwgaoJv2tzEjX6gGo/olSsASIJIOy+8KSUvPjzR5zDios+CmLrRzIGC9zZz8VQR4rwKz1QoK8ia5D+Tlv50/mjRMTxlMnxnafqecNwFFQZBp6/+Fn+o/+Sr4SWcFPWVafVdlJrBVB5sQxof4BjBcm5DXCBgB4ovdVkQ0InFLj/7156q1NAKyLwEoxb3nWj/q3Xi/flhVEkggWh6FEUVDgNT/hNTYkC/9FQSqrf0HVFUHc8EUUhAaAJAlXD1Af0l+yx5zzt48fDPaezq4Ab47uHCllA1afc+Hqcy703zbwvpVXdh7Kj5k4VTBO5s0TeaNg4vCu0aF3m8QFza16c6sOU4OppZqOiRdPHNw+f0xXRPpXzeqzVg7sPtF/sn/unJl6ul9P9zuvObj35vBsgLWy37/6h+Vf0LYPOBCcjQFOGxB2YwAsAr3zrKW1j/qxIm9YXftBXeJtA4Ja7htsA0ApKrUBlP5ETVgCRBKGtSugnnS/MTZtXqdIBZynHQvwEc6uAG+O7hyxlgNVOkGob9fI2htXAbjkQ9ds+vmzJqDBNIEFranjLW2w9BWYpt4y89X8yCJg2lavEwe3z5p/sf8DK8XkiM+bxLv/+toTAPR0v2kAlrZvwfbnllx8zV7xdrAVQRXpfhvWRWBBnUdirQiCY7RoNI0BqUyzmNbvk+o2BvhvP6h7XIuC1A/8u+KnMYDSn6iMZppm3GcgdcidX78h1Pt3ZULfGRwZNun/86deLxTGPvbB1eLdYD2A4NDZQY7qkx5AtAoIrG7BaRKmrjR1AGIzsVhPtqLDZRaQajYgl8t1d3d7fBQW6Q/g/74q1H/xXdNAUzojRoUO9BW7PqQBkITaHAzgBz/fDeDzH3Gp5nrgkWdtr4gZoCHRZ0koOTcM3L/xEQAeNiDXk+te013pQ63rulCuYsdPuX/ZNILwAN5rBxoHvWksQOkvpgBFkwFw4moDAlT/HAFEwoAZAJIwZNQ/vJ3BkWGT/q6Ekgo4bgA4MDuYCkBbKsA5bNSWSShiTj193onz5y5rOXpiFACwLz+yyHZtUlIBTulvRU9rAIy8CWBWtr1/YNfxU16R9bBnBI2On0pp5f8EiGGgfTtH5vleG1cp1plCEfQHB76uy2cFkbg5W4cFqcx+Y6JZz4SyPixibNkABv5JIqABIInBWfAT1L6w6PGW/s5dYHvMOYGnAhYcN4LyAACO7hwptWcA002CMdYi1b+s9hELywTp7D4ANhsg5oSqbANyuVwp6W9FT2v5UaO/rxfA7BmFkyODrpuGJYHPCKoIuQgMk3H6kGyAsyIIISwOKyu+K13XxcFBVWDdGmFMNAOoJxtQ6KL6J8mABoAkAO9a/2SlAvxE/V0JMBUgRwwtOD6C4FIBZTmyBQDmLgN8zNNMZ91TAVDPBngH/m0M9PXmR40BYF7nLAAzsx3IFk6ODHp8SgTrApxYpb+ViG2ArSJow/p1VTcG+BffYhxtsOqf0l9gVf+SGm2A3AIWO62Tsf/B0FYIExIUNABEaXy2+SYiFeBT+heMfEov+R9msKkA4QTOPYwDc3SP/QABPMgye/TorlGf431cUwGopCJooE/UeY/6v74wMQrfHsOP9BcNAPIwkhvPuxzAE3teBXDm7CM3Lr3GewRQlDaglPqXRGYDXFMBz78769UjJzJ7/Jb+VyG+vT+Fgf8qcJX+VhKdDWidXvbTkQZoA4ja0AAQRaliwo/KqQD/gf+P3VhGHIc0IEhvDrIiyErZzQPeVFcRZFPbVVzvcXF3d3eFUf83AaRbit/edIueHy3GLNet7ADwRC8wKe7L2oAIPIAtEl+KWBoDnn93FoB5c2Z95PIV9z30KABvGxC4+GbgvwrKqn9JEhsDWksU/dMGEJXhHgCiHLXM9S+7Lyx6jLGWqst+PBA2IFhEc3CAGOPZGtW/RNgAGycObhfK3spAX69NzVuvd75Y6nrXmwtyudzZHU0+1f9Hz17kfPG3Lvtgpu0NqYo+ddM18kNl9f0Tva/+6PHn/Dy6RmwD+10paxICPMALJ1pfONFqveCOW9cu7GrJ9eRcP73suq7Os5ZWVEcU+MaARsD6c+4TY6JZZAMqIpYRQK1z9pdS/5KOdNEJEKIUHANKwqKKSaABzvVXIRUQhu53ElQqQG+eUnK1pwKC0v1OnBVBmAztl9L9oqrH5/XOi2FJHVgD/0J3eoSf+y367183/TLdoo+eKnzuvTfZ9FCpTbquqYBje4vBUatnqI57/uPllJb+0q2ry15ZSuVvNrYDWLviihpPUpafPrd0fHjKnZqFFgDtp3Zj8vtvSwVUOrXTOaTfNqyTNT/VUan0d1I2GyAbAKI3AGWlv5MqsgGcAUpCgraUKEHgK73i7QqIRvoLVBsQFJ70F5RqDk5l3L/nmdbdhYGF/q8vdf+te45hes2PkJuuNqDfof9+67IP/tMzj7V0vpFpm7p5KekvcFYESfUfMa4VQUL9R8C//NvYrPloatUBCBswMNinZ45/ZM2N8po7bl2LSRuwetm53jd0qnnvXV2M+ldB7dJfoGZjQBXSX8CiIKIONAAkZkLd5ht9V0CU0l8S8a4AWSlk+2jY0l9SqjnYSaZ1t//rxcX5cbsHEBL/07fc7PpZZaX/9Ptr4m1v6W/lxqWXP9H7alzS34q0AZFJf8mJgzsAzJq/QtiA2ZkC0OW87GPvXQrg/o2PAii1qc1DzTttAAP/1RGU+peUsgGxhP+rVv8S2gCiAjQAJDZClf6SyDxALNLfSo2pAGMsa60CEthsgK1JQH40MulvxVvWCzVvu97PxekmLT9uips/8Yt9mC79jx/YAWB2icLxUurfqof8S3/Bsb1jq/SLsbRMc3A0PPXWJrQAw/E8/cTBHWecNw9AqkkfH5r2o2j9zm9YvxZuNqDSdV0M/FdB4NLfitUGWEd/Jkv9S2gDSLzQAJAYiEb6S8IuB4pd+kvCSAXAsznYGMueexgHgm9I9otT1tuk/+wlzZhcNObqGazXz55U50d3jeZ6cjd+qPusjqa8owD++IEdNg/gR/pb7++fl4e2XtG2Ev5mBIVN366RecuyTa0pAOPDhYifrmeOHT9wDMDsBRevXfEe+brrN3/D+rUH+kdzuVx3d3elgXyw7KcqQlX/EmOi+fw+A01R58QClP5WaANIXNAAkEiJWPpbCSMVoI70txJGV4ArUwvFjhkADsyJZ6qYkPVmfpmr9BfMXdaC6TbAdr31YtHp++nJcn/nOipYUgE+pf+cJc2zD1Ws/gUvD20FIG1A7B4AQMQ2QM9M/TzfsOhyTHowj4IrAAu6WjasX/vwC73YdcjnxoBKofQXRCP9AZzfVwxGGOPNAPSobEBI6l9CG0Cih1OASIhYBwHFKP1tBGIDQpX+T7/+KIDrLlpb430qtQHOEqBSSOlvIy4PACDdpMm3PQLtwgOUun5yyM9UzY+189VpA2yzYiSuNT/3Pv1oKqMVxs07r6/gX/aRbS/Lt4UHQOV1RDbu+883M+mWgaG+lJae0T43Xxj/rbWL/HziA488K9+et6z4M3DD4jJbw2rkgUeeFUkbIf2tOL//8js/MXRBlyWK72djQEVQ+kuiV/82dqZnhvfQsKW/E6sN4AggEh7MAJDQUUf6C2pMBUQT9c80BXCTMFIBpaS/IN5UAHzU2FhTAfCU/gLvrbROain3L4tIBay7pKaxm/f95xuZdKuup2bPWAhNg2lm0qn/79H9t6+1z0rypm/XyA2LLgtvEZiVdHbfDYsuc9ZiWXF85/cD+0eOfUC8Yh0TVLsNoPoXxC79BeFNCope/YPZABIVNAAkRFST/pLqugIiLvh5+vVHa08CBNgV4C39rSw4ZkTvAfLjphD3frBdmcvlnNLfim0rrfQAhYkxGYT2Od2/FjJZHTUvA9a1FGCapmlqpmbChAnT1PWK/xbcsOgyTA4FCnUVgHgQHAbMGv4v5buyc54E4LQBVXsASn+JIupfEqwNiEX6W+HuMBI2/BEjIXJ21jw8opW/Lib8pwLUrPX3T+0Dgir9lFhSAUd3jfr3AIJSgX8nHqmAyKQ/5CqAiptai/yfjZubMm2aUdB0wIAGmDABGEbhX36++3MfudDPTaQiRyTbAGxbCDy++aW+89k5T0oPAOCOW9daNwYUJsYwOfzHG6p/gWrS30ogNiB29S9Y3MYKbRIiNAAkXM7OmgCUtQFlUwFJl/6S6lIBVUh/K9HbAFHb48cG+Jf+Vmw2ID+y2FuA5np6AHSvWVPRU6xI6Y8gFoGZpmGahmEaugkD0CByAKZhFgyzfDtvxNLfitMGmPll8ptf1nTZUgHWjQHvv/ZqACcO7PDwAJT+EpXVv6RqG0DpTxoHGgASBUlMBcQl/UUHMIBMUzBVQFYqSgXUqP4l0VcEeduA6qS/FVkRlM6+BegoLf1Rm/pH0IvACsZEwZgAYJopXTcBTZQDGWa+UJgo++niC49+EZj1AJi0Af7Vv0TYgCPbit0OYmPAD368EUB39xqxAsxmAyj9JWpK/x1mySUAldoAqn/SUNAAkIhQPxVg9QB1E/h34icVEJT0l6hTEVS23N8nViVaSoDWKP0FYhHYEwhm9KdpmhP5MTNlapqum+niSzANIz+eH/Jzh9dbdsa1CEwiDVgVW9UwfVIQgA3r1wG4f+Mj3d1rMLkJWK4DC/LcSUZN9e8HY6LZjwdQQf1T+pMo4RhQEi5/+4d2DaSsBxAMHV0S7wFEBkBMAZoYB4KYB1qKaNYFWIllQJCwAX4C/8f2juXHjEAm2+R6emwGoIoxoLbAv9wA8Kmbrqn6YPf8x8saNAC6li4mAGAaRv6rH7+y7Oc+8MizcvqndQNAgE3AQWVObJRKoeTHDNlOcP/GRwAIG4DSM14bDZWlv0f430kpG6CC9Ieb+v/dP+2J5SSkQWAGgESNsuVAIuofxr6wqsk0FT1ASES2MkwSSyrg3+55dO7ylrLSX77dt3Okdg/QvWaN8ABS0SJVwae7CtZAlgF/9TeuuOfBlwEUzKmaHz/qXyCWAQMIYxGYtWXC6aCqxruASnYVy1QALDagwVFW/Vck/QWuFUHKqn9CwoYGgMSAauVAtoKf6oaEBoJsAIiMAOeE+ieyroBcTw6TO309ZL1TIIoKk9ptgFXF9j7t6x+3bLl/LTNABV/9+BUAvvvj5wB87ZMVJxPkMmAATa2poDxA7Q3TTvz3TjhtQCrT0t3dHeBhkoWy0h9VqX+JtAGU/qTBoQEgsaFCKsCj1j+WVMB1F62N3gOgHlMBVukvcXoAb4FYNhXgXa8yLfzvA59qNagxo1VIfyvCBnxm3bWBHEYQsfqX30nnjNEN69elMs1iTFAD2gBl1X8t0t9KS2efz96AUKH6JzFCA0DiJMZUgJ8231hSAcIDDPYjncENl4ZV/e8krlQAQrABuZ6cTfpLZGjfp9r2SAXIiHWup6dUvYp/RevnPGFsGKgauQgsqJaJ2m8i8S/9Bc4Zo6IxQIwJun/jo43jASKT/gih39cP1sB/eCuEy0LpT2InhoY8QmwIGxAZxlhLRUN+hA2IkvC6fssibEDECBsQCLmenIf6l0ip55O+nSOunyL0ffeaNdZg/7G9Y6Wud+XY3jE/glVB9S94dMfLgdzTapas30zx/XR+yBWf30zX1+ctz0ozk86+lWl7Q6jhDevX5nI50URe30QZ+I9d/UuMiWbhBCKD6p+oADMAJFz+65/3OAcBOYmmHKjq4Z4xdgVET0JTAa41P8FSNtr9k396rHtNt+16j9L2iGt+bPzo+YcBfOrqj1X0WWHsAnPV9N1r1tg6swHs6nsBpbsFqpb+VuSMUSsyFYA6rQiq+8A/yvX7RpYN8Kn+OQKIhA0zAEQVzs6a4aUCKo36uxJ9KuCxl2PoBxAkKBUgo/6BqH9viW8L7VuV68ULXUrq+3aOLJv3XrhpXJ81P6EG/isddCnV/2Zje7DrwGzh/4sXXuP8/uRyub5doyLfgunf0rKB/4q+k/OWZ9PNLn8cN6xfW3/ZAJnoiIAYA/8+W35DzQYsbjMZ+yfqwAwAUYvAUwHBrvRiKiBsKk0F+Cn48YkUiK4xYCsitC/LfqzSM9eTsyYBBMvmvXfe8mw38IPnH7vz+rWJK/eXCHcUVM2PFdlEkevpObZ3HAvdL+vu7hb/NFbDEEjg34r3DeupMYCBf1fCyAZQ+hPV4CIwEjp+SoCc1G4DQt3mG4EHeGrLoxPjuPmK2PoBJNHvC4MPD1BjzY81xFtKIJat4//1c08DsCp+YQDyYwYmV49ZZaJrXNlJNOr/R88/nGnGxFgFVUBPvbVJvl3pIrAHtx0AkB+fuO3y85wfnbRS45j+/RTkxwxr0F1+S8t+P2uX/mJbsCuJrghKqPSvaApQIIM+a7cB1Ul/lgCRsGEGgChKLamAUKW/QKl9YWGjWiogwHJ/b4FYNhXQvaZbHMb9o5VLw8gC/6IBoFKq2AAgdb94t/+ddwEXA1AsoCoR+Iflm+m//CbYwL+T5DYGJFH9VzoANKgx/zVmAxj4J8pCA0DUpQoPEIH0lzRUORDi2BUAx8qwYDt9fbaEwjMVIDyALWidbtZFEiDYwwRLpQ0AEusy4HeHxzodf0eE6Md03f/lde8F4Kr+XZW3/K46v5O5XM5bcIct/a0kywYkUfojjsC/jepsANU/URkaAKI0/hcFRCn9IyPTFPcJphNjKuD+bU8j0CE/FQn0sjbAlgeYs6TZ/xjQsKX/sb1j+TGjVHNzphk/ev7hSmcBiVRAaoEOYEQ756HXD9960dm2YD/K6X6UVt7W7+euvhdEI7UfopT+VhJhA5Ko/uMK/Lvi3wZQ+hP1YQ8AiYLq2gCseHuAGNV/eBmAx195NOJdYP6J2APkcrnP3HITgP2zAx5cVukSK5ust9agi4i1TYB6XC+IQP3D4nbE1yvqf2QGwH8bwAOPPFu87fA4gCZtAYBZi1MATKNYDtT/zrsAJnV/mYN5I745sj9YfDOt4X/b9zMM9e/RA1AKBfuDkyj9oUDgvxTeHqB29c8GABIBzACQZFAqFVCXgX/1iSwVIAq+PzMZ+F943AjWA3gs+nXFIxXwiS/eXNH10Uh/G4Es7hXqXxufN4FxAEd3Ye6yrEX3uwf7y57Niu2bIzyAXKpQ9vraD1ALG9avVSoVQPUfOKVSAQz8kwRBA0CShLUrgNI/dkLtCrBJf8nC4waCTgVUKottzcFl1Wel19eIt7rt2zlydNfI3GVV2oBjw+PauF2ZHd018slVl/r5HlYxAlWMW5XS/1NfXYfpnkop9S9QpCKoEaQ/Ilf/EpsNoPonyYIGgCSMs7Pmof5aQ5gkKMJIBZSS/lYUSQUc2zvmU31Wen11+JS2t733Y//2wsOZZggb4LP+56HXDx/vnyVzcCf7jk7/+KKy38OqB/Y7l/4KT6Wg9LcSrw1oBPUfl/S3ImzAeV2jcR+EkMpgDwCJgtp7AATG2JS2OOy3xzJcwu4BUGQVQFmC8gCy3N8ngXcFoPLGgJDwbt51vb7Uh1w7nu976uF0Bt/40qcqOpUMvX//0Rfli19ae5X1GueZY999VrX0r6IHwJUoGwMaQfpDDfUPYHHrlIjSm4JxmOwBIBHADABJBlbpLzg7q4QHaLRhoKWoPRXgJ/DvJPBUAAIqlK8Fq1r1k5qoJbBddReETfSXumfs0t/nGcImssaARlD/ikh/TFf/AIzxZgRnAwgJFWYASERUnQRwSn8rKngAQRgeQJ1lwP6pwgNUJ/1t1EcqwCZVbZH7WiLrzkZkkQG4/f1T9T81zkRyEvim3kqpXfoHlQGQhGcDGkH6Q2H1b6NqG8DwP4mG4P9kEhIUxljWW/0DODuLs5Wo10C267DIBjQ4e8w5Ihsg8N7bmsvlRM1Pjeofk83BweJ/ln8glFWrtvNUFFz3I+4r/XprNEjqq/8w2LB+7Yb1a8VPvsdl/hceCxpB/bfO2a+I+l/canqrfwDGeLNICPiBgVgSPSwBIipSVvfbUKQcCEC26zDLgeBjQFAgUX8bIQ0IQvipAP9SVZynbGQdbvK67DozBDoXtaKzBUtQ0j/w8L8kwP7gRpD+SE7g34bPoqDKNt4TEgQ0AEQtKpX+EpEHUMEGBNgVoOYWMJ9Y8wA2Ku30rYhk2YAwotTe8jpeG1Dd3B5RChXUmFF1kDagag/QIOpfESqS/lbYG0AUhCVARBX8FPyURZFyIEzaAOKsCApV/UsSUREUvfqXxFIRVOPUzrLnSZb6l/ipCHKSaXsjMvV/fp8RlPrfYc6rQv2rEP6vWv1LKioKIiRsmAEg8VO77rfCciAF2WPOOfirnyDomh9vVE4F1NK86329f+Yuz6bL/QUIKhUQ1MD+UudJqPSXVFoRxMB/xNSu/iXMBhBFoAEgcRKs9JfUZTlQchGhzU/fcjsA4N2In67anFCfUtXWvOttA2opqY+gIijwdV228yRd/UusNqAUUUp/UP0HKv2t0AaQ2GEJEImI//rn00abBVLw4w3LgRThrBlNn77lZvF2r3lG9AdYeNwIvCKob+dIFRVBPgP/pfp3S11f6TGchFQR5Pq1eHBs71hF/dAVXZ8UNqxfu6CrxfVDEQf+4y37UYGQ1L/EWRTEGaAkMpgBIDEQtvSXMBUQI5OB/5sB5HI9ALq712DSAyzVpqUCzPDnYKiQCnh5aCuAK9pWun600ubdYGfpeKcCNhvbAazFFQE+0Ur96fjqEP/ViCoga0UQA/8RE7b0t2KMNzMVQKKHi8BIdPztH66JTPrbUMEDCBrBA1il//TXe4QH1uj9nAAARNxJREFUENg8QGTEuDLskW0vizecHqDSSHmN6v9n2x8+/g7Sacw6Ax9a/jHbR202QKh/AGtXhGIAyqp/20I0iZ9xqLUQ3hhQV3K5nLMB4P6Nj2Zad3evqXKRYqWoKf0jbgKOUv1b0ZvGmAEgkUEDQKLj7q9+KtV2Kq6nq+MBUL82oJT0t1wwzQOgwWyANAACYQPCHorv5NHdD6czOLQP6TTOWYRCATcudvcAUvoLAjcANTZD15MBcFX/MvB//0OPAAjbBqip/hGtAYhL/QPID878r//ww7ieThoNGgASHXd/9VMAYvQAUMkG1JkHKCv9Jf/fo/tSelrTdBOmYeQ/c/PCxvEANgOQyeo3Lr088DN487PtDzc1I5VGKgVNg2nCNJGfwE1Lp3mAp97aBGB8uGB9MVgDUFb9O62RzQaEbQAQeRLAirPsJzwboKz0F0RjAGKU/gDygzMB0ACQyGATMImawtCMwtCMuJ7OzuAwEMFLP+r/gUf3p1NNup7R9UxKz6RTLT96/FCveUYDNgdnsjqAJ3pf/dHjzwV7Bg8eePZh04RhwCigMPk/w4Bp4qHXHpaXCfUPoKk11dSaCvwYZZt3S3UPh72S2UnExffyoa7P3XDruu41a3I9AVeJKK7+oyHewL9Q/4RECQ0AiY677vmRfDteD6CIDch2HU66DRALjD59y81nzShfx3L/f74BTTNhovg/ANC01L8+sgcxDQhCHCvDMlldqH9E3vxqGijki/8reoA88hPI52FYvg19u0b6dk19CQF6AD9ze8o2Q0dsAyL2AN6PW9DVsuHWdbmenkBsQCJG/YQd/l/casar/uXbDP+TKOEUIBIbhaEZMZYDcV9Yjfiv+ZGYME2zYBiABk0zJ18x5AQg1wFBERDZyjCp+xHT3Jt8Hvk8NL1Y+TNVApRHfsJ+sfAA85ZlEZAHqFH6WxHf2DC+h0IQvzlv2g+DFOWhVgT5dxobbl2HmiuCGPiHGmU/hMQCDQCJE5EHiMsGKOUBkJyugCqkP4Dv/eTZbPNMQzN0XTOgaQBgmqZpmoZh5K1X9ppnxNIVENKcUFhswI1LL3+i99UYR14WJjA+BtNEKoVUGppWrP8p5DFa4r+Fvl0jwgPcsPiyqp/rv9k32HtWhFUQn99n2DyAIDwnUEWeoWobkCDpH2r4X5HAPyGxQANA4ifGVIA6iwKQkFSAKPip4hNN0zSMfEFLmTB1zRRNwDBN0zQK0w0A6isVgOnrAlbpF2Mpnuh9NdhHCP5t097bLlviccEXbvrYvzz1cKEwZQBMA6aJiXHcscY+CEhy0ejyWk4VYODf5w2rwKmJ5SuuTiBAaiwxkjbApweg+gcD/4TQABBFYDmQQOVUQHWBf8nXPvm+f3zwJRPQzbSupTRNQzEFUMgXRl0/pc5SAdaRNWL4T4A24KHXD4+Pjnqrf4FpwACMAibGARQLgYyC+8U3LJqK+rsWNXmTUOlf6oIwnEBQDQYbbl1XNhUQoPQH1X+1UP0TRaABIKoQezkQmAooQY3S30qhMG4YE5qW0jRd6H/DzBcKjvLzSeosFWBDVATVeJOHXj8MwKf6B/D5Gz8G4AdPPCyaMKDh8x9wj/1b1b/E5/LjRNT8oEJNXKouqDoC7y32rghi4B+U/oRY4B4AEiliFYA3XBQgid0GBCj9Bf/44MvQihOATJgaYML86sevyuV6ANh2hFmJa1cAgrMBHkPrq9sFJqQ/gPHRUQA+DYAf/Ewy9bAB9RH4d0UagBp7AMKeLGS1AQz8C9RX/5wCRKKEBoBEjR8PgFhtAD0AQpD+ku/95DlAAzTA/J1PXA1AqH+BhwdAwtcGuxqAGqU/QlD/kipsQF0G/q3UbgCiHCp6/0OPLD1qrPH8b8o/0Yz6CckAqN/vS/VPIoYGgESNTwMApgImid4DiMVefkb7B/GsHin6y+YBkORUgNMAVKH+v//YS2fMP1e8LaQ/gBOHD3/1I++r5WylqMgD1HHgX1KjAYhS/Yuv9ED/aE+up3YPENmgz8ANgPqBfwENAIkY9gAQdWFnsCDKzuDwAv9+6O5ek8v1WC2Bk1JdAdY9YiGZhACbg6sL/AvePXgIQOcZc+QrIal/TIp7bxtg6292pYqvN9Qpn9GTaXsj15MD0L2mO4LHyS92QVfLHevX3bfxEQDV2YDkzvhHctQ/IdFDA0CUhp3BkrA7g2OU/lbFLzxA2U+RA4Jc9weH1zpcS3NwfsxIN+u1SH8AX7r5SlH/8+7BQ8IDhFH8Y8OPDfCgDgL/NfLsS9+P7FmuX+kd69cBqMIGJFf9U/oT4g0NAEkATAUIQkoFRCb9XUP7rorfOwkgcJX+tgtUSwXUqP5RHPc5pY9PHD6M8A2AYN7ybKUegNJf1PyIqH+uJxd2+N/7i63IBiRX+oPqnxAfhDvkjpCgEKmAuDi7gtHnoSNsQFCIxV6RBf79RPfLSn//9JpnlPUJ1bHwuCGyARVRdRBdINX/wLvvAhh491h4xT+uzFue9b8HoP7Uf6UzQK0V/6L+JzzO7zN8frF3rF93x/p1PZ7/JVL9Vw3VP0kKbAImMeC/D9gJO4MlNaYCoq/58ejxtYX8/WQAKiK81uHqUgEVrdMSSPV/22WLq3hisNicjK0HoP6kv8RnE7Cz2dcj/F97b0B1X6xrKiBe6V9jB3BypT87gEn0sASIJAyWA0mq7gqIpdxfxv5LifvARb8V1boCfK7Tkiil/uHZFVDH6t8nrurf9Uqr9K+uQKiWr9RZEcTAf9Uw8E8SBw0ASR6xewAokwqotCsg9iE/KFEFZJ3/46dMqDpC7QpAhTZAqGc/NiAM9f/UW5sAGAUTwI1LL6/uJjYbQOnvMeWzlLi3vl6pBwjki5U24HVjXveaRBqAeKU/qP5JMmEJEImBWkqArLAcSFLWA8Qr/W14JAHEG+GlAgRKVQR5ewCh/k/29X3lQ1fXcK4phPQXCAMgqNoGVEeo6l8ssgjqtiIuvkLrE++WqgIqpf5LyXrb65UWAgVodWTg37o/OBaqKAGqj8A/S4BI9DADQBJM7KkAdTyAdzlQlIu9aiFs3S/xmQoQrqkiKRlsKiBU9W/jid5Xo/EA0QT+g/IAUhzvMOdJD2CjivVerkVBPtV/sFkOa9nPhlvXHegfzfX0xOgBKqI+1D8hsUADQJJN7B4AyqQCXMuBlAr8S0Sdj3UBcGTSX+KnK0AoyCqkZBVzQm02QAz7Hx8du+2yxUAAlT8e0l/yRO+rCDMVUJ30t+pd5xye8Gp+ShXEn99nyGP4kf5+in/8E0bg38qCrpYNt66LPRVQFpb9EFIjHANKEk9haAaHhErkkNBcLhfxiM9KiazgxwM/Q0K7u7uFj6qIWuaETlf/AeBH/UuEDQicKtS/c7SleEW+6F8NV/ov6KcdtqLAf64nJ6P+zvC/n+p//4M+/eD9BW64dd2GW9flenpyPWE15NRC7IF/qn9SB7AHgMRDUG0AVuJtCYAyqQChddZf9/m4D1KGWAL/pRCpAKtMtEX9qy4pqTQVsHHnEQAzF2mBqH9v6W/tARAImf6pm66p/dG2e1ZKLWLX9o9VUSmXtzIWVUD+FwL88MVdmq596ooLpx2v8ur/yKS/kyizAWV7AOoy8M8GABILLAEi9YPIAzR4V4CI+gMAqhwSGhnqqH8AveYZh371Y1jKfpzXVOcBKuoK2LjzyPjoKIDrs7Wq/4qi/oIwqvOrC/wH9fRKuzj8qH+f/PumPelMU7ajQ9P0jTsPG4XCb1w8f+pg0z2Ah/oPr+LfJxtuXQfg/oceib0iKPbAf4xPJyRwmAEg8RBGBkDSmNOBSpX7K24D1EFkJGRXgFPu195X6m0DpPr/zdVT6r+KlWHwof5vWHyZfPuJ3ldtMj2QDECM0l/6t6Ckv8A5CKgUP3xpd1NLi55K6amUpmmmacJEfmLi4ysXFE9oqQKKRv3XPuM/7FSAd/i/jtU/MwAkFtgDQOqQ2FsCIu4K8C73l10BxIZz4UAu19NrntFrnuGq9atrBrDi0RXgqv5RYtmWB0+9taki9Q9glX5xRY/wQ7yBf0Gw6t8//+fxFzVNMw3TMAzTMAzDNA3TMA1oeOCFXcWzrem2vWEjyop/n8TVGLC41axj9U9IXLAEiNQnDVIO5HPIT9U7g+seax+CtSSp15yDyqPIfnCtCCql/gU+V4b5qfmxSX8p08Xkn0Daf2OX/hWV/Xy3Z2fgpWh6KmUUjIJe0AFAJABMmKZRKFgvS0rg34asCEIkjQGU/oSEBA0AqWfqe0iopdy/PJXuDG4cXHuR5SuiMSBwbHNC3z14qJDPew/7L2sD+naNAJi3rOQFVvXvKtNvXHp5LR4g+mbfUvhX/wihGd0oGEahoOnFf9+iAzBNo1Ao5PPenxt7xb9PImgMqMt+X0LUgT0AJDZCbQOwUn/TgWqZ7k8PIJHKz0MC5nI9S7VjtpEyAeYEAtwc/MAjz05dM90GlAr8l2LOkop3xsUe+Bf4DP/vMOdVMYXWZw/AP/7iueZsa7opo+spPS17AEwjXxgbHfnCDZeV+sSkqH8rAaYCrD0AjaP+2QBA4oIZAFL/1FM5UO2LvRo2FSAEn6vasy0ms9FrzjnX3+ZgP9z70+133jJVc1/7yjDJZ9ZdKz1A364R4QEqlf6oXP2rE/iHv9i/VP/i3z3wM3zlQ9f8n8deMg1DT6X0/JQByOfz4yOjrp+SROkvCKMiiGU/hEQADQBpFJJeDhTsTt9G6wqwBvthsQHydav6t10j3ugN0gNsu/OWS+S7Fc0JlfTtHPHuCujbNXLDokYJ/PtEKGMPKxgUpmkWCoV8Pq9pmjQApml+5cMu45WSq/4lETcGhAfVP2kcaABIAxGvB0C1qYBgpb+kMVMB1qBvqQCweN0pE8Xa4Nrrf1J6k/PFAFMBAKT0Fz6h7gP/fohM/QP40tqrvv/oiwDMySpb08SX111lu6wOpL+VWmyArP+JMfxP9U8aChoA0lioUA6ESlIBFXX6VkEdpwJKVfVYC35KCUEPgVhLKuDen273+GhQqQBb4L9v50i62eWebx/aqOs46+z1DRL4x+SPhHB3tdT/WL+WUv0AX1prl/seN6md2NW/pJb+4LjUP6U/aUC4B4A0IvEuCgBwdtZ916wVOd0/7MNkuw434K6AWoq/xa6A6j43pWcA3PvTbaUuWHjc8FgX4ErfzhGRDbhh0WU29e/KsXc2jpzaOG8WLr68eea8R4YHNvp/1rG9Y5Wq/2BH2leKTf0D6O5eI9W/zelV8VMhvrqKvsDAZ/yro/4lPjcGRLxSwBWqf9KY0ACQ2Ljrnh/F+HQVPEApvBd7hURdegCrnrO+HUgFSNUewA+VegD4Xhl26ODG5gxSGs5c2qzr0HU0Z3DqxMayn1iF9EfcgX+rMrb9o1f0MyB+eMQNa1Tb9Rr4d+J/cZj3DuBQiVf9cwQQiRGWAJHGRcFyoJDK/X1ST+VAUu6LuG9I816EB6iuIsjWCuykuoogb55/beP8M9C1sLkpjXwBugbDhGlC0/BG78YLlq4v9YmJk/61fHrZCaHW+8vZoGVpHOlvRdn+YAb+SYPDDABpdNRJBUQf9XdST+VAQvdbX7ElAYKyBD5TAdYGANc+YFeqSAV40zG/eWwCU/8bx8g4RsdLXp/EwH8tny5Lg6w/PLWnjBpT/UtkNiDugxSh+ieEGQBC4k8FvPFiDvEF/p3UQSrANtbTmQQINiFQSyqgLEGlAuYsae441jw2gXQKhgnDhK7DMGAYGJvAiJsHqGPpb/sBKBX1r31qUINLfysbbl0XeyqA0p8QAQ0AIUViGRIqan4+c8tNAADz7REt4gOUIuwhoQ9vebilFakUoME08MHzPhbIbZ2TfzzmfgY+C7LSAUFlq4CsVDEn1IoY9TM0itMjME00pTGRga6hYBYNwMDwtOsTOuXTP66bH0qNhS17t1KzgKj+bTgrgqIcAEr1T4iEBoCQKSL2ALlcblL6Fzknq5AHQGipgJ9ufTjbhlS6aABg4ql9Dw8N4qOX+LUBHot7ndjmfoY6Cb5UKsB7AKhPqk4F5MeKMrRgYGAY43k0ZdAsDIABw8DwGI5P/uDXvfS34fGzZP2Qa4rAowEg8G9IHah/ibQBrXMOAEtA9U9I5NAAEDKNCMqBrFH/XE+ue0239aPnZE0A6tiAwFMBD/z64c5ZAADRfgqYJqChqaXKG1ZkBhD+Eij4SwWk9KbPf+TCKm5eXSpArAu4pXv9489tHJ3A8Bg0DboGwwA0FAzcesN6NJ76h7+fB5sTcH7K+X2GNQnAwH9ZXt5231d/uxu46L6HHl3UZi6ueb+eB5T+hDhhEzCJk3gngXoQXmdwLpfr7u6Wgf/uNd25npzzMmED1CHAzuB0GkYBhTzyeRQs/zMNPPjKw9XdU6x28ijrD2kKkAe2XQF33nLxnbdcHNTNq9gVgMl1ATddsz6fh2miYGCigIKJiTzWXru+6mbfuNR/2PPvbULf/88P1X9ZXt52nwh8LGo1/3+337ymu7un3F6UqlFW/XMGKIkXbXJPOSHxcPdXPxX3EUoSbB5gern/9A/15ADYUgECdVIBgtpTAT989uFsG9IZpFLQU9A0mCZMA/k8Rk7jk1f5qgJyRmHLjm6MEWs24J7/eCWlp7+0flVQN68iG2DbHIykNfsifFnsrBMrVTlmqwISDj+QM9Sl9M/letpmH5Dq3/qh+zY+CmBNoKkAZdU/aABI3LAEiJCSBFUO5CH9Ba7SX1B/XQH5CeQnAMA0oBvFJmDTRCGPiYnqbytj/KGW+FdHpc3BFVFFRZBYGSZsQAPW/PhE/Ag5u0dKIf4zp/r35sOfWCKK/hc5iv7vWL8WwdkAlaU/ISrAEiBCylBLOZDY6fuZW27yUP9lqbNyoHweY6MYH8PYGMYt/xsbxfDpCu5TSo1J3VbLIQPHVhEULFVXBCWr5geRq38nzp8rcaQA1X/YpU0x0uZj4+8d69fesX6tKOmr+kFU/4SUhQaAkPJU5wFql/6Sc7KmUjagln1hn7/xY/k8RoYxOoyRYYwOYXQYI0MYGcKda/1OAfIO8DtXgClCeB4AIawMcxKv9I9FFvvpHglW/dd+EzWxqn9n+N+GtAFVPIjqnxA/sASIEF9UVA5UtuanOuqmHMjIQ08Ve38BCC3wuQ9UvAqg0vk/KrDHnJMyw/rFG9TKMCf1XfHvjW2VhO2juVzPCm2a+q+uDaBBpD98qH/JHevXVlQRROlPiH9oAEjM3HXPj1TuA7ZRdlFASNJfoqAHQOWdwZ//4McA/PMvH4ZZVP9fvMld/XsIL9fQbFL8gGpdAd40Qs2PN+UyTt013l+RLzMM/JT9eOC/MSBZ6p8dwCR2aAAIqYxSHiBs6S9RbVEAqk0FfOGDdtHvOnjRowbDuuELyVH/grA9AIJIBTRy4N8PtbeaqP811kKN6l9S1gYkS/0TogI0AIRUjK0cKDLpb6U+UgE2XMP8rq9bL0hiIVA01GIDKP190t29BnDZB5ybrF/3yA8k6MuslKCkvxVXG0DpT0h10AAQUiUiFSDqfc+e0RT9AeomFVAW7xn/SfQA//jgC1/5+HtDTQJIqqgIovqvkVJtwVZXUAdfZinCUP+SO9avPdA/2pPLrenupvonpGpoAAipkp5i4P+T6baBUB/ksSYMSqYCavQAVjVvK7EoJfRlmVCybEBk+E8FUPrXSFnpD2CHOfeM5H+lroQq/SULulpu/8Cnw1gcRkjjQANASMVMSv+bxbv5oc6QPICQ/vDcFAYlPQAqLAdyVv+7jvL0KLlOqPSPJgkgKJsKoPqvCMcPbQ5Ad3d3zm14pbQE3+3Z6fS3Cf3pteFH/fsfAeSBCPwHuziMkEaDBoCQCrBJf0kYHsA78G+jnsqBSnX9qrbbK4mUSgVQ+geC9zigHeY8Z3ZL/LQnrobNSTSxfziK/mkDCKkOLgIj8XPXPT+K+wi+6MnlPnPLzU71L8gPdeaHOiM+kg2lloWhtn1hUu4LecQKnwCxrQyj+q8RsaTMj/qX71p/npP+U902Z79N/cvUZbDkB2eWKvqvZXFY9HAGKFEBZgAIKU+pwL+TAFMB3Wu6xd9R61/TsgkBNVMBj2zc7VHP4z3jP+nyqCxiPXBkhUAC4QFaYw0BJV36234y5Zezw5zb7fa6/JR6crNS+ock+iV++n0rXRxGSCNDA0CIF/6lvySMciCh+0Uo3E9RkHpdAUde3PzAVas+Y31RiiHX2p4kzvaphSibAVQg6erfg+7uNTscqTjbD3nZH2z1f/htUX/5e8nn76iK8D/thxVBhPiEBoAQd6qQ/hJRC+TfBnj8ybR+SOQEEuoBADg9ABw2QHHRQ2qnjqW/N9bwvxXnqKvozlQtpSr+A88DVDfokzaAkLKwB4AQO6Lk3KPc3ycVtQS4/uHsXtNt0/oVhdbOyZrqdAV0d3d3d3e/uPmBUl0BzoRAo5kBUQtUx4ha+bhPEQO2cH6phXdISHWQd7+vRyyj0gfVOOZfNgYkpTeAkChhBoCQaYj9MmfNaA7kbuFNCPWPUqkAOSTRmQqA8ronAuq4EKgxpb/A4wfbtTNY2fofb+nvnckU/3dRm+ndLS0JasmXdXFYIDckpD5gBoAogQqDgGTgPyj1Lyg7HUj+1fQTIasuw65CKsC6AxXAi5sfiPEwKtNrnlFnqYCGDfyXxRbvd919gemDsGKkrPr3/pDMZ7ruSbDiMe2nOhZ0taiTCuAIIKIIzAAQUlO5v0/KpgLkzB8ntterbrALOxWQy+VKxfZk4N/6t//FzQ90d3fXuDY4cXzlN67wc1ndpAIo/Z2IAL/Pah/rZXFlBnzO+Pf41SQ+tKjVXFQuDB+s9LfCxgBCrGimqUqJMGlw7v7qp6J/aATS30rZcqAwBmjYCMkDyDWo3hdYr5Gf0mgeoCJCtQGteohJYEr/UpTtcikl9GPpEPCj/j22FlrjF5/78PXe9wlP/duI0QYwA0AUgRkA0riIgp8on+hnOpDVA4ThB2JcFGCzBzItINqCaQNcSWgqgOrfg7IKXp0GAP/7fUv9prL+NvNIEkYm/QUyG8BUAGlY2ANAGhFZ7h/L0z1aAsIO/0tqbwnI5XJla3nLYlUDVe8MrnuS1RXAiv/AsVb/W71BqF0Bzv2+HkxT+SVKGT1+uUWs/iXqNAYQEj3MAJDGIuKan1J4pwJk4D9UP1BjKkDE78tW/ljxiP8JmArwIBGpAEr/kIi4+Me/9PfATwIzLukvYWMAaViYASCNQlDT/QPENRUQWRJAUEsqQIz2h4+xHvBtEsBUQGlUTgUw8B8szqh/ItS/c3WJZN9L9nxF7Opfwo0BpAFhEzBRiJD6gBWJ+pci9kUBqLklwNngGwhMBZQiqFRAUE3AlP6BY+sDdmYAwsgJBBL4l8jO4EWtJhwJQHXUv41QswHsACbqwBIgUucEu9grDPx0BodNIOVA8DELqCKyXYfpAVwReQAVKoIo/SPDY39wIASr/jE52njfSz37xLuTvxaUlf4CLg4jDQINAKlbFA/826iDncGyHChAG1CXHuDfXnj4tvd+rPb7xN4VQPUfHtZ9wGGvAAtc+kuccz8VV/8CsTiMjQGkvqEBIHVIsqS/RBEPgNoqgqw2ICgPgLorBwrQAyCOVAClfwTIZWFwBPsDtAThqX9R+WMlEepfwv5gUt/QAJC6IqHSX6JCORCC2BkcbDMA6jQVEBQRpwKo/iPDo8gnkPqf8NS/jWRJfyu0AaReoQEg9UOMo/2DRZFUQCzLwjywpQKcw4IS4RD+7YWHM03B3zaaVAClvwqU2hNcEZFJ//qAi8NI/cExoEQh7rrnR9V9YryLvcLAY1lYSDjHgZ2TNWvfFxY42a7D4n+uH4r+PFXzby88HPg9Qx0SSvXvQUVrs2ohkOKfiNV/csP/NmocFcoRQEQpmAEgySbpNT8eRFwOVCra7zMVUEvNz4EDGzMpnHXO+qrvIGGlUBipgDCk/7+98qZpGJ+68sLA7xwxVjEt3x46tjCMZ9U++jP6wH/dqH8BK4JI3cA9AEQt/K8CqGPpbyP2ciBBGBVBh9/e2NmGpgzSOkwT+QKaOtYHcmc1bYCI+osSoIlxAAikFdgVPx7Azx6AYNX/vz63I9verqdSup4CTNM0J8bGP7l6cYCPiJJSejoMA1B75U+U6l92ANeZAbBSqQ1gBoAoBTMAJHk0jvQXqNASgBC6Anr3bpzTiVQKKR0pHaYJTcPIwMZs5/rab65+KiDTVPQAIVF7KiDwwP8/P/lKx6xZmq5rmq5pGjQNppluavq3V9687T3nB/usCIg4mp4g9S+pY/UPZgNIwqEBIAlD/cVeYVA304GspFIoGMjnoWswTZiAacAE3n574zkBlQNB1VRAZFQ9ICiMsp+mbNY0YRqGCc0AoAEmYJp6KmF/iZLVQZus0yYOLg4jCSVhv3ZJI9NogX8nKqQCal8UIPjlcxsXnImxCcCEiWIGwDAxkUe+EMRBJ1E8FRDUQgAPKk0FhNfsaxqGUShAgwnopglRA2QahhHoP3nIJEtPJ+u0CYWLw0gSoQEgCYDSX1I3qYCJPMYm0DRRjP0LA1AwMFHASNCFMYqkAsIY++MfPzYg7Dk/hYKRKhQADaZm6qYGzTQN0zQL+cK9j79w503vDfXptZMsMR3jaZ0rwBoBVgSRZMEmYBInmubyE2jtA6b0L0XsHkBQtQ34aW7jnE50ZNGcQVNmMgNgYDyPgSFcsXJ9oMcsoogHsO4B+I3Lwg3/O7F6AGsTcARTPu/95ctNLS16Kq2nUrquAzBNwzTM/MT4hvdfEvbTa8S/ng5pBFBFxOtVGqED2BunDXB2ALv++SMkMpgBIOrSmOX+PlGhHAg1pAJu6V7/y+c3FgpobkJTeqoEaGwCx08FfswisacCbnvvx2QeIHrpL3CmAiIb8G8YhfHR0VQ6rafS0gAYhpEfG4vmANVRqZi2XR+9H0hWpqIuYWMAUR8uAiMqIhd7Uf17kB/qjH5fmJOql4UVChjP49QQ3h3AuwN4ZwDvDmBgCB96//pAD2gn3n1ht733Y4P9GBmK8QiAZWVYlOu9vnTze03TzE9MjI0Mj40Mjw0PjQ4Pj4+O3nnTlZGdoVJqF9OR7QiL+FnEG9EYUMviMEJChRkoEjO2NKimaTcvm8uan4pQIRWAqsqBfvHMxnQKhlmcBwNg7bXrgz6XOzHmAe576uF0Bre/P54MgJWUnon+od9/7EUx89U0TQ340lpFS/+DVdIR5AHUkf6iBKhh63+c3Lfx0Z/v6LP9paP6IvHCEiCiCpqmARC/E++/6464j5MkklsOFHaw34PYy4Eali/dfFXcRyiPOmLaJ4k7cEPxs+1HMP1vHCGxwxKgIt/73vc0TdM07dprr437LI2ICIfI34wb7r4v3vOQ6jgna1ZdERQL8ZYDETVJlphm2Y/ifOLPfiDeEH/jhA0gJHZoAIrcfvvtBw8e/OxnP7ty5cq4z9JYiF+IzqAIPUBySZwHoA0ggsSJ6WSdtgGR6l9S6k8eIRHDEqAinZ2dnZ2d+/btu/322+M+CykiPADLgZJIsDuDI0DxfWEkAsIT02E0ACgr/RtzCYATp/QnRCmYAZjCNM2tW7deeumlcR+k4RARkVKJUaYC/KDCOCAbSSwHYiqgMWHgPyi4AUBQSv2Lv3QM/xMVoAGYYv/+/adOnbrkEtX30dQl3sWR9ADJJVkeAOwKaDyUFdOlUPbAjP0LPNS/tdWNkHihAZhiy5YtS5cubWtri/sgjYvHb0Z6gOTCVABRkyQG/pU9sFX9N3L436Pyh9KfKAV7AKbYsmULO4BVhi0B3ogqIBXmgbrCrgCiFMoq6VIoe2Bb4L9h1T+L/kmyYAZgii1btqxatSruU5AyMBXgjYLNAJJk5QHAVED9oqyYdiUpgf9GhuqfJA4agCm2bNnCDuBEQA/gjeIeIIk2IIzb/suTD4dxW+KNymLaFZVPS/UvoPonSUTpEqCP3/WdkO784N1/bHtlcHBwz549LAFKCiwH8oblQMHCcqD6QGUx7YqyB6b0F1D6k+TCDECRbdu2dXV1LViwIO6DkApgKsAbpgIChOVAiSaJgX9lD0z1L6D6J4mGBqCIqP/hju7EQQ/gjcoeAMnsCoj7CKRilFXSpVD5wFT/Aqp/knRoAIp89atfzeVycZ+CVAM9gDf5oU6VbUASPQBtQFJQOY7uisoHXtRqllX/DTICiOqf1AFK9wAQIrEmZ5zTlNkSUJb8UKfKLQEA2BVAgkVZJV0KlQ/MwL+A0p/UDcwAkMRgTsKFwdWhch4AjZcK+NwHPhbgYYgVlePopVD5wD7Vf92H/6n+ST1BA0ASgE3x0wNUjfrlQEm0AZV+yh03fOz291P9h4XKStoVle2Kn7IfQSOrf03T2EBIEgcNAEkq9ABVo7IHQOOlAkiAKKukS6Hygf1L/wZX/5gMS9EGkATBHgCSAJwhf48kANgS4AOVWwKQwEUBYFdA3KispEuh8pkZ+BeULfuRPWnef5UIUQ1mAEhicP5u9f5ty1SANywHChzmAeJCZSU9dGyh80WW/SSCKor+6QFIUqABIKqgTeLzeucsICf0AGVR2QOA5UCkHCor6VKofGBO+5FU1/Lr5w8TISpAA0DiR+h+MeEHJSIoHh/yhh6gLPQAgUMPEA0qK2mJ9ZCK2xWqfwlj/6TuYQ8AUQI/ZZSyy6rSEAtbAsoiPICyXQEJXRQAgF0BIaGsjJYaet/w1I+rsqeVUPpLKpL+zua0oI9DSFgwA0CShMwDVOEEmAooC1MBgcNUQBgoq6etMjpBkjpBRw0bn+rfWrBqWih7PbMERB1oAEjC8PPbthT0AGVhZ3DgsCsgQJQtoXFtnLW9KN7132IbDUodJl78q39Y/hJVdH2NJyQkQFgCROLH5+/QQH57shzIDxwSGjgcElo7akp/lNPQyipsZQ8WPRWV/Vgb0sr+VbJdJgpZ6QSICjADQNTCI0MaYPKUqYCyqJwHQGLLgZgKqJqEqn9lSeixw6CWaT/eVT1Ok8ASIKIONABEOVyjI4HnT+kBysJyoDCgB6iUZJX9JIKEHjsMqlP/Au/JdfKaqu9PSKjQABR58cUX165dO2fOnHnz5n3lK185depU3CciZYIrtUMP4AeVPQASmwqI+wiJQU3pj8Rq6OSaljCoRf1LrMEp6x8sj3F2tT+UkNqhAQCABx98cN26devWrXvyySf/6Z/+6amnnvr93//9uA/V0FgHLIT6oA1330cbUBb1PUDibADLgcrCwH/gBHvsRK8B/sSf/SAQ9e+N7e8X63+IUrAJGP39/V/4whcefPDBG2+8EcCll14KYMOGDXGfqxERvx+jkf5WNtx9H9uCvVF8UQDYGVxfqCn9kdjAP5J88sAJT/p7TwL1voCQiGEGAD/72c+WLFki1L9g1qxZqVQqxiM1LOKXYyzj0pgH8IP6qYC4j1AxTAXYUDbwj8Rq6OSmLMIggsB/Kaj+iVLQAOBTn/rUiy++aH3lX/7lX2655Za4ztPgxPgrkh7AD+p7gITagLiPoAQqS/+EauiEHjskolT/cnU9938RNWEJEDKZjHzbNM0/+7M/e+SRR1566aUYj0TiglsC/MByoDAQHqCRK4JUVv/B3nDfcEQ/nFT/klgC/8IDgLF/oiTMAExhmuZdd931z//8z0888cS8efPiPg6JDaYC/MBUQBg0ZipA2bKfRAf+E3ryMIi37Ifqn6gJDUCR4eHhT3/6088888xzzz13wQUXxH0cEjP0AH5Q3AOAXQFJQE3pjySHz5N78jCIUf0TojIsAQKA/fv3r1+//vLLL8/lcs3NzXEfhygBy4H8wHKgkGiEAUHKSn8kVkMn9NghQelPiAfMAODpp5+++uqrv/CFL3z/+9+n+ic2mArwg2sqQJ1FwiwHUhBl1X9yi2cSeuyQoPonxJtGNwD/+I//+NGPfvTuu+++9dZbDx8+/Pbbbx86dOjkyZNxn4soBD2AH4Tct/5Pvh7vwSQJ9QD1ZwOUrfhHkjV0xCdXfAsY1T8hZWloAzAyMvK1r33t1KlTGzZsmD9//vz5888999z58+d/73vfi/toRC3oAWpBKQ+QUBsQ9xECQ2Xpn1D1n9yThwTVPyF+aOgegGw2WygU4j4FSQZsCagFpVoFktgVUAdDQpWV/mDgv16g9CfEPw2dASCkUpgKqAWlUgFxH6EakpsKoPoP44lU/1ao/gmpCBoAQiqDHqAWlPIASbQBSewKUFb9x1g8Ix4t/1fdp4dxsLLkB2cq2ABA9U9IpdAAEFIx9AC1oM50IDAVEDLs9w2DGE+uoPQH1T8hVdHQPQCEVA1bAmokP9SpTksAAHYFBA6lfxhQ/Vuh9CekapgBIKR6mAqoBXXyAGAqIFAY+A8Dlv3YoPonpBZoAAipCXqAWmA5UO2o1hWgrPRHwtV/XI9WUPqD6p+QmqEBIKRW6AFqRCkPkFwbEPcRVA/8q6P+Kw2oU/3boPonpHbYA0BIALAloEbUaQlAMhcFAMh2HY6xJUBZ6Q/FAv+U/rVA6U9IUDADQEhgMBVQC6qVAyUxFRBLORAD/z6xBf7LKmyqfxtU/4QECA0AIUFCD1Aj6ngAJLkrILJnKSv9keTAP6j+HVD9ExIsLAEiJGBYDlQjwgMoUhGU3HIghD8klOrfD5T+NULpT0gYMANASCgwFVAj6qQCEloOhDBTASz78QnVf41Q/RMSEjQAhIQFPUCNqOMBkNhyoDBQVvpDpcA/qP5rhuqfkPCgASAkROgBaoSdwUrBwL9Pqhj0SfVvg+qfkFChASjy+OOPX3/99Z2dncuXL3/22WfjPg6pHzbcfR9tQI2o4wHQwKkAZaU/Eh74jxFlV/xS/RMSNjQAAPC///f/vuOOO377t387l8tdcsklX/rSl+I+Eak36AFqhB4gRlQO/CPJ6j9e8a2g9AcD/4REBQ0AhoaGvvWtb917772/9Vu/tXr16v/yX/7Lvn374j4UqUPoAWqE5UCxoLj0V0f9VxdNj0uFU/0T0uDQAKC1tbW/v3/dunXi3SeffPI973lPvEci9Qo9QO2o4wHQAKkAxdV/3EeYQk097YqaZT+g+ickWrgHAJqmpdPpgYGBn/zkJy+++OKPf/zjX/7yl3EfitQt3BJQO/mhTkW2BGDSAyi7KyDbdbi6bQCU/v6pUU/nB2emO04GdZiyz4rmQRVB6U9I9ChtAIb1WyJ71sGDBx9++OFt27Z1dHTMmDEjsueSxmTD3ffRA9SCUsvCoPa+sCqWglH9+yQQPU31H/cRCGlEWAJU5OKLL/7pT3/a29v7/ve//8tf/nLcxyH1D8uBaoflQP7xuRSM/b7+UVNPu8KyH0KIDc00Ffp9amPd/7MlpDs/8peXlvrQCy+8cPPNNw8MqBJZJHUPUwE1ok4eQKBsKgCOPEBKz1jfpfT3T4B6OuwMAKU/IcRJo2cAzj333O3bt1tfOXjw4IoVK+I6D2lAmAqoEaWmA0HtVEC267BrKoCBf/8oG013Rc2jUv0TEjuNbgBGR0e3bt0q3x0ZGfnzP//zz33uc/GdiDQi9AC1o5oHUNwGWN9VXPqrpv7jPoJflDUqVP+EqIDSTcAR8NnPfvb3fu/3TNO85JJLXn/99e985zuXXnrpnXfeGfe5SMPBtuDaYWewf4QHyDTFfQ5PGkT6yzsHWAukpvQH1T8hytDoPQD5fP4v//IvH3jggbfffltI/89+9rO63uiJERIjtAG1o44HgNotASobgAZR/67U6ATUVP+U/oQoRaMbAEIUhB6gdpTyAFDVBqhpAJSS/ohDT9diAKj+CSF+YKibEOVgS0DtsDM4oSil/pUto3dF2dNS/ROiIDQAhKgIPUAgqOYBaAM8YL9vLSh7Wqp/QtSk0ZuACVEW4QFYDlQj+aFOpcqBVO4MjhGlpD8U1tOuqHlaSn9CVIYZAEKUhqmA2mE5kOIopf6VLaRxRdnTUv0Tojg0AISoDj1AIKjmAWgDwLKf2lD2tFT/hKgPDQAhCYAeIBCU8gBo+FSAUtIfyuhpnyOAFDmtE6p/QhIBewAISQZsCQgEBZeFQdUhoeFB6V8Lyp6W0p+QBMEMACFJgqmAQGAqIEao/mtB2dNS/ROSLGgACEkY9ACBwM7gWFBK/SvbQVsKZU9L9U9I4mAJECHJg+VAQaHUkND6LgdSSvpDYTHtirKnpfQnJKEwA0BIUmEqIBCUygOgTlMBVP+1oOxpqf4JSS40AIQkGHqAQGA5UKgopf5Z9hMUVP+EJBoaAEKSDT1AUKjmAerABnDMfy2o7FWo/glJOjQAdh5//PFUKvXXf/3XcR+EEL9suPs+2oBAUMoDIOGpAKWkPxKo/uM+gjuf+LMfUP0TUgfQAExj165dt99+u2maK1eujPsshFQGPUAgKFgOlDgboGDgX1k97Yqyp6X0J6RuoAGY4sSJEx/96Ed///d/3zTNSy65JO7jEFIx9ABBoZQHQKJSAUpJfygspkuh7IGp/gmpJ5QeA3rGyk+Hdu/Xbe9PTEz85m/+5gc/+MFrr7129uzZZ511VmiPJiRENtx9H8eDBoJSE0IBnJM11Z8QSvVfr1D9E1JnKG0AouQP/uAPCoXC3//933/ve9+79NJLNU31P7SElIJbAoJC5AHUsQEqLwqg9K9XKP0JqUtYAgQA99xzzyOPPPKTn/wkk8ls27aNDQCkDmA5UFCwHKgsVP/1CtU/IfUKDQCeeuqpP/zDP/zpT386e/ZsAFu2bKEBIPUBPUBQKOgBFLEBqvX7guo/OKj+CaljGt0A9Pb23nbbbffdd9+KFSsAFAqF7du30wCQuoEeIChUmw4EBVIBCkp/qv+goPonpL5p6B6AU6dOffSjH73tttsuvvjiffv2Adi3b9/o6Gg2mzUMQ9cb3R2R+oAtAQHCzmCJguo/7iPUCZT+hDQCmmmq9UvcyoYfXhTSne//9OsAHnzwwU984hPOj3Z2dp48eZJ9wKTOoAcIEKVsAKrtDM40VfMsSv86huqfkAahoYPcH//4x83p/NEf/dEnPvGJ/v5+qn9Sf7AcKEAathyI6r+OofonpHFo6BIgJ6+++mp3d3fcpyAkLFgOFCAKlgMhzCGhqkl/UP0HB6U/IY1GQ5cAEdKw0AMEiFI2AJV4AP8lQKqpf0r/AKH6J6QBaegSIEIaFpYDBUjdlwNR/dcxVP+ENCY0AIQ0KPQAAaKgBwjEBnDMf31D9U9Iw8IeAEIaF7YEBIjwAEqVA9U4JJTSv46h9CekwWEGgJBGh6mAAKmPVAAD//UN1T8hhAaAEEIPECSqeQBU2BWgmvQH1X+gUP0TQkADQAgR0AMESH6oUzUb4NMDqKb+84Mzqf4DhOqfECJgDwAhpAhbAoIlWYsCVJP+YOA/UCj9CSFWmAEghEyDqYAAUS0PgBKpAKr/+obqnxBigwaAEGKHHiBA1CwHkjZAzX5fqv8AofonhDhhCRAhxAWWAwWLauVAAM7Jmq3NcR/CAaV/gFD6E0JKwQwAIaQkTAUEiIKpAKVg4D9YqP4JIR7QABBCvKAHCBZ6AFco/YOF6p8Q4g0NACGkDPQAwUIPYIPqP1io/gkhZdFMU632r2l0Lw7rzrm3wrozIfULWwKCJfaugNh7ACj9g4XSnxDiE2YAAKBQKJx77rmahe985ztxH4oQ5WAqIFgaPBVA9R8sVP+EEP9wChAA/OpXvzIMY//+/bpedEQzZ/IvEyEubLj7PuYBAkTB6UDRQPUfLFT/hJCKYAkQAHzhC1/o6ur627/927AeR0h9QQ8QOLHYgFhKgCj9A4fqnxBSKTQAGBkZmTt3bk9Pz9KlS1OpVHt7e1gPJaS+oA0Ilug9QPQGgOo/WCj9CSHVwR4A/OxnPxsdHf3t3/7trq6uGTNm3HTTTW+//XbchyIkAbAlIFjqviWA6j9YqP4JIVVDA4AHHnjg3HPP/aM/+qNjx45t3ry5v7//C1/4QtyHIiQZ0AMES70uC+OSr8Ch+ieE1AJLgPDOO++0tLTMmDFDvLt169ZLL7301KlTHR0dYT2dkPqCtUCBE005UDQlQJT+gUP1TwipERoAO/39/TNnzjxy5Mi8efPCejoh9QhtQLBE4AEiMABU/8FC6U8ICYRGLwG68sorX3zxResrL7300ty5c+fOnRvXkQhJKCwHCpaklwOx7CdwqP4JIUHR6Aagubm5p6dHvjsyMvLNb37zW9/6lqZpMZ6KkIRCDxA4CfUAlP6BQ/VPCAmQRl8E9lu/9Vu/+7u/29zcfMMNN+zevfvb3/72VVdd9ZWvfCXucxGSVIQHYDlQgAgPkJR9YZT+gUPpTwgJnEbvATBN87vf/e7f/d3fHTx4cMmSJV//+te/8pWvyH3AhJCqoQcInMA9QOA9AFT/gUP1TwgJg0Y3AISQ8KAHCJxgPUCwBoDqP3Co/gkhIcFQNyEkLNgSEDhqdgaz3zcMqP4JIeHBDAAhJHSYCgicQFIBgWQAKP0Dh9KfEBI2zAAQQkKHqYDAUSQPQPUfOFT/hJAIoAEghEQBPUDgxFsOxLKfMKD6J4REAw0AISQi6AHCIBYPQOkfBlT/hJDIYA8AISRq2BIQONW1BFTXA0D1HziU/oSQiGEGgBASNUwFBE405UAs+wkDqn9CSPTQABBCYoAeIAxC9QCU/mFA9U8IiQWWABFC4oTlQIHjvxzIfwkQ1X/gUPoTQmKEGQBCSJwwFRA4wZYDsewnDKj+CSHxonQG4IPX3B3SnX/53F0h3ZkQUgXMA4RB2VRA2QwApX8YUP0TQmKHGQBCSPwwDxAGtaQCGPgPCap/QogKpOM+ACGEAJMegKmAwMkPdVY6JJTSPwwo/Qkh6sAMACFEIZgKCIOK8gBU/2FA9U8IUQoagGn8wR/8wdVXXz0yMhL3QQhpXOgBwsBPORDLfkKC6p8Qoho0AFN897vffeihhzZu3JjNZuM+CyENDT1ASHh4AEr/kKD6J4QoCHsAivznf/7nH//xHz/99NNz586N+yyEELYEhIVrSwDVfxhQ+hNClIUZAADYvHnz7bffft999y1YsCDusxBCpmAqIAys5UAs+wkJqn9CiMrQAODYsWMf+chHxsfHb7vtts7Ozu7u7gMHDsR9KEJIEXqAkMgPdVL6hwTVPyFEcRrdAJim+cUvfrGtre3HP/7x22+/vWXLlpGRkc9//vNxn4sQMgU9AEkQVP+EEPVp9B6AH/zgB6+//voLL7wwe/ZsADNnzrz33ntXrlx56tSpGTNmxH06QkgRtgQQ9aH0J4QkhUbPANxzzz1/8id/ItS/QLQBTExMxHcoQog7TAUQZaH6J4QkiEY3ADt27Ljooousrzz33HNLliyxWgJCiDrQAxAFofonhCSLRi8Bmjt37tatWy+//HLxbn9//7e+9a0/+IM/iPdUhBAPWA5E1IHSnxCSRBo9A3DnnXf+t//23+6///5t27b93//7f6+99trzzjvvd37nd+I+FyGkDEwFkNih+ieEJJRGzwDcddddmUzmO9/5ztGjR1etWvWNb3zjc5/7nK43ui8iJBFsuPs+5gFIXFD9E0KSi2aaZtxnKMkHr7k7pDv/8rm7QrozISRi6AGqpjXDYEeVUP0TQhJNo2cACCFJhy0BJEoo/QkhdQDDP4SQeoAtASQCqP4JIfUBDQAhpE6gByChQvVPCKkbaAAIIfUDPQAJCap/Qkg9wR4AQkhdwZYAEiyU/oSQ+oMZAEJIHcJUAAkEqn9CSF2i9BjQb/xdKqQ7/6/fL4R0Z0KIOjAP4A3HgHpD9U8IqVdYAkQIqVtYDkSqg9KfEFLfMPxDCKlzWA5EKoLqnxBS99AAEELqH3oA4hOqf0JII0ADQAhpCOgBSFmo/gkhDQJ7AAghjQJbAkgpKP0JIQ0FMwCEkMaCqQBig+qfENJo0AAQQhoOegAiofonhDQgNAAAsGTJEm06M2bMUHlDAiGkRugBCKj+CSGNCnsAAOCZZ56xyv2vfOUr8+fP1zQtxiMRQsKGLQGNDKU/IaSRYQYAAM4555xzJ9m9e/drr732V3/1V3EfihASBUwFNCBU/4SQBocGYBojIyNf/vKX//7v/76zszPusxBCIoIeoKGg+ieEEBqAaXznO99Zvnz5b/zGb8R9EEJIpNADNAhU/4QQAvYAWNm6des999yzZcsWXacvIqThYEtAfUPpTwghEirdIoVC4Utf+tKf/umfLliwIO6zEEJig6mAuoTqnxBCrNAAFLnnnnsKhcLXvva1uA9CCIkZeoA6g+qfEEJssAQIAA4dOvTHf/zHTz31VCqVivsshJD4YTlQfUDpTwghrjADANM0f/d3f/fOO+9cvXp13GchhCgEUwGJhuqfEEJKQQOAhx56aPPmzf/jf/yPuA9CCFEOeoCEQvVPCCEeNLoBGBgY+PrXv37PPfe0tbXFfRZCiIrQAyQOqn9CCPGm0XsAOjs733777bhPQQhRGrYEJAVKf0II8UOjZwAIIcQnTAUoDtU/IYT4hAaAEEL8Qg+gLFT/hBDiHxoAQgipAHoABaH6J4SQitBM04z7DKXp0cK68xqFv2pCSBKog5aA1kziY0CU/oQQUgWJ/+1PCCGxwFRA7FD9E0JIddAAEEJIldADxAjVPyGEVA1LgAghpFYSWg6U0BIgSn9CCKmRRP72J4QQpWAqIDKo/gkhpHZoAAghJADoASKA6p8QQgKBBoAQQoKBHiBUqP4JISQo2ANACCEBk5SWgKT0AFD6E0JIsCTjtz8hhCQIpgIChOqfEEIChwaAEEKChx4gEKj+CSEkDGgAijz77LM33HBDV1fXypUrX3nllbiPQwhJPPQANUL1TwghIcEeAAB48MEHf+/3fu8v/uIvVqxY8Q//8A9bt27dtGlTWI8mhDQYyrYEKNsDQOlPCCGhQgMA0zTnz59/3333feADHwBw+PDh5cuXDwwMhPVoQkjjoaYHUNMAUP0TQkjYqPjbP2L6+vrefvvtyy+/XLz78ssvX3XVVfEeiRBSZ7AcyCdU/4QQEgE0AJg7d+7ZZ5/9xS9+8ZlnnnnooYe+9rWvfe5zn4v7UISQeoMeoCxU/4QQEg0sAcLo6OjXv/71e++9V7x71VVX/epXv2pubg7r0YSQxkadciB1SoAo/QkhJEpU+e0fF/39/dddd93x48dfeeWVwcHBV199dWxs7Itf/GLc5yKE1C1MBdig+ieEkIhpdAPwh3/4h3Pnzn3ooYdee+219vb2yy677G//9m9/8YtflLp++fLld9yhSvSOEJJQ6AEkVP+EEBI9jW4AfvKTn7z//e8HcOmll4pXhoeHFyxY4Hrx6Ojom2++Ka8khJCq2XD3fQ1uAz7xZz+g+ieEkFhodANgmqamaXfdddfFF18MoFAo/K//9b8+/vGPu168c+fOQqFAA0AICYqG9QCU/oQQEiONbgA++clP/v3f//0HPvCBoaGhn//859ddd51hGP/9v/9314u3bdsGYOXKldGekRBSzzSgB6D6J4SQeGl0A/A3f/M3+Xz+1ltvXbhw4be//e2Pf/zjv/zlL8fGxv7u7/7u+uuvnzNnTnNz87Jly7797W+Pjo5u37593rx5Z5xxRtynJoTUFQ3lAaj+CSEkdhp9DOj4+Hh7e/sf/dEf/cmf/Il45bHHHtuwYUN/f/+6deuuuOKKdDr99NNP/+IXv7juuutSqVRzc/MjjzwS1qkIIY1NxBNCIx4DSulPCCGKkI77AF6cfP5DId155priG7t27ZqYmJBl/Q8++OBv/uZvXn755T09PRdddJF48a677tq4ceOtt94K4Jvf/GZIRyKEkA1336fOloBgofonhBB1aPQSoC1btgBYtWoVgAMHDtxxxx2LFi16/PHHpfoXrF+/fsOGDbAMCyKEkDCoy3Igqn9CCFEKGoAtnZ2dYu7n3/zN3wwNDX33u9/t6upyXnn11VeDBoAQEj515gGo/gkhRDWULgGKgC1btqxatUrTNAA/+9nPMpnM9ddf73rlnj17mpqaLrjggmgPSAhpRIQHSHo5EKU/IYSoSUNnAEzT3LJliwzq9/X1zZw5M5vNOq8sFAqPPfbYihUrMplMtGckhDQuiU4FUP0TQoiyNLQB6Ovre/fdd+Vc/xUrVrzzzjtvvfWW88q/+qu/2rZtGzcAEEIiJqEegOqfEEJUpqENgOgAXr16tXj3tttuA/DFL37x9OnT8pqJiYk//dM//c53vgOuACOExEHiPADVPyGEKE5D9wBs2bIllUrJgT/f+MY3XnzxxQcffPCCCy74zGc+s2jRop07d/7yl7/s7+//9re/fdddd4lhQYQQEjFJaQmg9CeEkETQ0BmArVu3Llu2rKWlRbyr6/qPf/zj//iP/7j44ov//d///Rvf+Majjz764Q9/ePv27a2trWAGgBASK4qnAqj+CSEkKSi9CfjkX3w4pDvP/NZ/hnRnQggJlQDzAAFuAqb6J4SQBNHQJUCEEJI4VCsHovQnhJDE0dAlQIQQklAUKQei+ieEkCRCA0AIIYkkdg9A9U8IIQmFBoAQQpJKjB6A6p8QQpILDQAAmKb5z//8z93d3TNmzLjgggv++q//Op/Px30oQggpz4a774vYBnziz35A9U8IIYmGTcAwDOPTn/70zp07v/nNb65cufLFF1/85je/OTEx8a1vfSvuoxFCiC823H1fNG3BlP6EEFIH0ADg+9///ptvvvnMM890dnYCWLlypWmad999Nw0AISRBROABqP4JIaQ+YAkQ/vqv//ov//IvhfoXrFq16siRIzEeiRBCqiDUWiCqf0IIqRsaPQNw4sSJvXv3XnPNNdYXt23bdtFFF8V1JEIIqZowtgRQ+hNCSJ3R6BkATdMAHDhwQL4yODj4F3/xF1/72tfiOxQhhNREgKkAqn9CCKk/Gt0AzJw587rrrrvzzjtff/31gYGBRx999L3vfe/KlSvvuEOVLZuEEFIFgXgAqn9CCKlLNNM04z5DSU7+xYdDuvPMb/2nfHv//v2f/exnn3nmmWw2C+CMM87YtGnT7NmzQ3o0IYREiUc5UGumZAyI0p8QQuqYRs8AAFi4cOHTTz/d39//ox/9qKWl5Wc/+xnVPyGkbqgiFUD1Twgh9Q0NQJEDBw587nOf++EPf7hy5cq4z0IIIUFSkQeg+ieEkLpH6RKgyOjr67vqqqu+9a1vffnLX477LIQQEgrOWiBnCRDVPyGENAI0ABgeHu7u7u7u7v6f//N/xn0WQggJF6sNsBoASn9CCGkcaAAIIaSxkB5AGgCqf0IIaSjYA0AIIY2FrSWA6p8QQhoNGgBCCGk4pAeg+ieEkAaEJUCEEEIIIYQ0EMwAEEIIIYQQ0kDQABBCCCGEENJA0AAQQgghhBDSQNAAEEIIIYQQ0kDQABBCCCGEENJA0AAQQgghhBDSQNAAEEIIIYQQ0kDQABBCCCGEENJA0AAQQgghhBDSQNAAEEIIIYQQ0kDQABBCCCGEENJA0AAQQgghhBDSQNAAEEIIIYQQ0kD8/wFdH2pnINloFwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<PIL.Image.Image image mode=RGB size=1024x768 at 0x1CB1B076898>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<gempy.plot.vista.GemPyToVista at 0x1cb1200d6d8>"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gp.plot_3d(geo_model, show_surfaces=False, notebook=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Geomodel plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<PIL.Image.Image image mode=RGB size=1024x768 at 0x1CB38F68278>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<gempy.plot.vista.GemPyToVista at 0x1cb1200d3c8>"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gp.plot_3d(geo_model, notebook=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Interactive plot\n",
    "\n",
    "Passing the `notebook=False` keyword argument will run the pyvista visualization in an external window, allowing for interactivity:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "tags": [
     "nbval-ignore"
    ]
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<gempy.plot.vista.GemPyToVista at 0x1cb38f683c8>"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gp.plot_3d(geo_model, notebook=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Granular 3-D Visualization"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Plotting surfaces"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style  type=\"text/css\" >\n",
       "    #T_33c5f46c_9914_11ea_8fb5_5cf370744477row0_col3 {\n",
       "            background-color:  #527682;\n",
       "        }    #T_33c5f46c_9914_11ea_8fb5_5cf370744477row1_col3 {\n",
       "            background-color:  #527682;\n",
       "        }    #T_33c5f46c_9914_11ea_8fb5_5cf370744477row2_col3 {\n",
       "            background-color:  #4878d0;\n",
       "        }    #T_33c5f46c_9914_11ea_8fb5_5cf370744477row3_col3 {\n",
       "            background-color:  #5DA629;\n",
       "        }    #T_33c5f46c_9914_11ea_8fb5_5cf370744477row4_col3 {\n",
       "            background-color:  #ff3f20;\n",
       "        }    #T_33c5f46c_9914_11ea_8fb5_5cf370744477row5_col3 {\n",
       "            background-color:  #443988;\n",
       "        }    #T_33c5f46c_9914_11ea_8fb5_5cf370744477row6_col3 {\n",
       "            background-color:  #728f02;\n",
       "        }    #T_33c5f46c_9914_11ea_8fb5_5cf370744477row7_col3 {\n",
       "            background-color:  #ffbe00;\n",
       "        }    #T_33c5f46c_9914_11ea_8fb5_5cf370744477row8_col3 {\n",
       "            background-color:  #ee854a;\n",
       "        }</style><table id=\"T_33c5f46c_9914_11ea_8fb5_5cf370744477\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >surface</th>        <th class=\"col_heading level0 col1\" >series</th>        <th class=\"col_heading level0 col2\" >order_surfaces</th>        <th class=\"col_heading level0 col3\" >color</th>        <th class=\"col_heading level0 col4\" >id</th>    </tr></thead><tbody>\n",
       "                <tr>\n",
       "                        <th id=\"T_33c5f46c_9914_11ea_8fb5_5cf370744477level0_row0\" class=\"row_heading level0 row0\" >0</th>\n",
       "                        <td id=\"T_33c5f46c_9914_11ea_8fb5_5cf370744477row0_col0\" class=\"data row0 col0\" >Fault_1</td>\n",
       "                        <td id=\"T_33c5f46c_9914_11ea_8fb5_5cf370744477row0_col1\" class=\"data row0 col1\" >Fault_1</td>\n",
       "                        <td id=\"T_33c5f46c_9914_11ea_8fb5_5cf370744477row0_col2\" class=\"data row0 col2\" >1</td>\n",
       "                        <td id=\"T_33c5f46c_9914_11ea_8fb5_5cf370744477row0_col3\" class=\"data row0 col3\" >#527682</td>\n",
       "                        <td id=\"T_33c5f46c_9914_11ea_8fb5_5cf370744477row0_col4\" class=\"data row0 col4\" >1</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_33c5f46c_9914_11ea_8fb5_5cf370744477level0_row1\" class=\"row_heading level0 row1\" >1</th>\n",
       "                        <td id=\"T_33c5f46c_9914_11ea_8fb5_5cf370744477row1_col0\" class=\"data row1 col0\" >Fault_2</td>\n",
       "                        <td id=\"T_33c5f46c_9914_11ea_8fb5_5cf370744477row1_col1\" class=\"data row1 col1\" >Fault_2</td>\n",
       "                        <td id=\"T_33c5f46c_9914_11ea_8fb5_5cf370744477row1_col2\" class=\"data row1 col2\" >1</td>\n",
       "                        <td id=\"T_33c5f46c_9914_11ea_8fb5_5cf370744477row1_col3\" class=\"data row1 col3\" >#527682</td>\n",
       "                        <td id=\"T_33c5f46c_9914_11ea_8fb5_5cf370744477row1_col4\" class=\"data row1 col4\" >2</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_33c5f46c_9914_11ea_8fb5_5cf370744477level0_row2\" class=\"row_heading level0 row2\" >7</th>\n",
       "                        <td id=\"T_33c5f46c_9914_11ea_8fb5_5cf370744477row2_col0\" class=\"data row2 col0\" >Sandstone</td>\n",
       "                        <td id=\"T_33c5f46c_9914_11ea_8fb5_5cf370744477row2_col1\" class=\"data row2 col1\" >Strat_Series</td>\n",
       "                        <td id=\"T_33c5f46c_9914_11ea_8fb5_5cf370744477row2_col2\" class=\"data row2 col2\" >1</td>\n",
       "                        <td id=\"T_33c5f46c_9914_11ea_8fb5_5cf370744477row2_col3\" class=\"data row2 col3\" >#4878d0</td>\n",
       "                        <td id=\"T_33c5f46c_9914_11ea_8fb5_5cf370744477row2_col4\" class=\"data row2 col4\" >3</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_33c5f46c_9914_11ea_8fb5_5cf370744477level0_row3\" class=\"row_heading level0 row3\" >6</th>\n",
       "                        <td id=\"T_33c5f46c_9914_11ea_8fb5_5cf370744477row3_col0\" class=\"data row3 col0\" >Siltstone</td>\n",
       "                        <td id=\"T_33c5f46c_9914_11ea_8fb5_5cf370744477row3_col1\" class=\"data row3 col1\" >Strat_Series</td>\n",
       "                        <td id=\"T_33c5f46c_9914_11ea_8fb5_5cf370744477row3_col2\" class=\"data row3 col2\" >2</td>\n",
       "                        <td id=\"T_33c5f46c_9914_11ea_8fb5_5cf370744477row3_col3\" class=\"data row3 col3\" >#5DA629</td>\n",
       "                        <td id=\"T_33c5f46c_9914_11ea_8fb5_5cf370744477row3_col4\" class=\"data row3 col4\" >4</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_33c5f46c_9914_11ea_8fb5_5cf370744477level0_row4\" class=\"row_heading level0 row4\" >5</th>\n",
       "                        <td id=\"T_33c5f46c_9914_11ea_8fb5_5cf370744477row4_col0\" class=\"data row4 col0\" >Shale</td>\n",
       "                        <td id=\"T_33c5f46c_9914_11ea_8fb5_5cf370744477row4_col1\" class=\"data row4 col1\" >Strat_Series</td>\n",
       "                        <td id=\"T_33c5f46c_9914_11ea_8fb5_5cf370744477row4_col2\" class=\"data row4 col2\" >3</td>\n",
       "                        <td id=\"T_33c5f46c_9914_11ea_8fb5_5cf370744477row4_col3\" class=\"data row4 col3\" >#ff3f20</td>\n",
       "                        <td id=\"T_33c5f46c_9914_11ea_8fb5_5cf370744477row4_col4\" class=\"data row4 col4\" >5</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_33c5f46c_9914_11ea_8fb5_5cf370744477level0_row5\" class=\"row_heading level0 row5\" >4</th>\n",
       "                        <td id=\"T_33c5f46c_9914_11ea_8fb5_5cf370744477row5_col0\" class=\"data row5 col0\" >Sandstone_2</td>\n",
       "                        <td id=\"T_33c5f46c_9914_11ea_8fb5_5cf370744477row5_col1\" class=\"data row5 col1\" >Strat_Series</td>\n",
       "                        <td id=\"T_33c5f46c_9914_11ea_8fb5_5cf370744477row5_col2\" class=\"data row5 col2\" >4</td>\n",
       "                        <td id=\"T_33c5f46c_9914_11ea_8fb5_5cf370744477row5_col3\" class=\"data row5 col3\" >#443988</td>\n",
       "                        <td id=\"T_33c5f46c_9914_11ea_8fb5_5cf370744477row5_col4\" class=\"data row5 col4\" >6</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_33c5f46c_9914_11ea_8fb5_5cf370744477level0_row6\" class=\"row_heading level0 row6\" >3</th>\n",
       "                        <td id=\"T_33c5f46c_9914_11ea_8fb5_5cf370744477row6_col0\" class=\"data row6 col0\" >Schist</td>\n",
       "                        <td id=\"T_33c5f46c_9914_11ea_8fb5_5cf370744477row6_col1\" class=\"data row6 col1\" >Strat_Series</td>\n",
       "                        <td id=\"T_33c5f46c_9914_11ea_8fb5_5cf370744477row6_col2\" class=\"data row6 col2\" >5</td>\n",
       "                        <td id=\"T_33c5f46c_9914_11ea_8fb5_5cf370744477row6_col3\" class=\"data row6 col3\" >#728f02</td>\n",
       "                        <td id=\"T_33c5f46c_9914_11ea_8fb5_5cf370744477row6_col4\" class=\"data row6 col4\" >7</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_33c5f46c_9914_11ea_8fb5_5cf370744477level0_row7\" class=\"row_heading level0 row7\" >2</th>\n",
       "                        <td id=\"T_33c5f46c_9914_11ea_8fb5_5cf370744477row7_col0\" class=\"data row7 col0\" >Gneiss</td>\n",
       "                        <td id=\"T_33c5f46c_9914_11ea_8fb5_5cf370744477row7_col1\" class=\"data row7 col1\" >Strat_Series</td>\n",
       "                        <td id=\"T_33c5f46c_9914_11ea_8fb5_5cf370744477row7_col2\" class=\"data row7 col2\" >6</td>\n",
       "                        <td id=\"T_33c5f46c_9914_11ea_8fb5_5cf370744477row7_col3\" class=\"data row7 col3\" >#ffbe00</td>\n",
       "                        <td id=\"T_33c5f46c_9914_11ea_8fb5_5cf370744477row7_col4\" class=\"data row7 col4\" >8</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_33c5f46c_9914_11ea_8fb5_5cf370744477level0_row8\" class=\"row_heading level0 row8\" >8</th>\n",
       "                        <td id=\"T_33c5f46c_9914_11ea_8fb5_5cf370744477row8_col0\" class=\"data row8 col0\" >basement</td>\n",
       "                        <td id=\"T_33c5f46c_9914_11ea_8fb5_5cf370744477row8_col1\" class=\"data row8 col1\" >Basement</td>\n",
       "                        <td id=\"T_33c5f46c_9914_11ea_8fb5_5cf370744477row8_col2\" class=\"data row8 col2\" >1</td>\n",
       "                        <td id=\"T_33c5f46c_9914_11ea_8fb5_5cf370744477row8_col3\" class=\"data row8 col3\" >#ee854a</td>\n",
       "                        <td id=\"T_33c5f46c_9914_11ea_8fb5_5cf370744477row8_col4\" class=\"data row8 col4\" >9</td>\n",
       "            </tr>\n",
       "    </tbody></table>"
      ],
      "text/plain": [
       "       surface        series  order_surfaces    color  id\n",
       "0      Fault_1       Fault_1               1  #527682   1\n",
       "1      Fault_2       Fault_2               1  #527682   2\n",
       "7    Sandstone  Strat_Series               1  #4878d0   3\n",
       "6    Siltstone  Strat_Series               2  #5DA629   4\n",
       "5        Shale  Strat_Series               3  #ff3f20   5\n",
       "4  Sandstone_2  Strat_Series               4  #443988   6\n",
       "3       Schist  Strat_Series               5  #728f02   7\n",
       "2       Gneiss  Strat_Series               6  #ffbe00   8\n",
       "8     basement      Basement               1  #ee854a   9"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "geo_model.surfaces"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "gpv = gp.plot_3d(geo_model, show_data=False, show_results=False, plotter_type='background')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'Fault_1': (vtkRenderingOpenGL2Python.vtkOpenGLActor)000001CB39AE6DC8,\n",
       " 'Fault_2': (vtkRenderingOpenGL2Python.vtkOpenGLActor)000001CB39AE6CA8,\n",
       " 'Sandstone': (vtkRenderingOpenGL2Python.vtkOpenGLActor)000001CB39AE6A68,\n",
       " 'Siltstone': (vtkRenderingOpenGL2Python.vtkOpenGLActor)000001CB39AE6EE8,\n",
       " 'Shale': (vtkRenderingOpenGL2Python.vtkOpenGLActor)000001CB39B12108,\n",
       " 'Sandstone_2': (vtkRenderingOpenGL2Python.vtkOpenGLActor)000001CB39B12D68,\n",
       " 'Schist': (vtkRenderingOpenGL2Python.vtkOpenGLActor)000001CB39B12E28,\n",
       " 'Gneiss': (vtkRenderingOpenGL2Python.vtkOpenGLActor)000001CB39B12EE8}"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Plotting all surfaces...\n",
    "gpv.plot_surfaces()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(vtkRenderingOpenGL2Python.vtkOpenGLActor)000001CB39B12888"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# ... masked by topography\n",
    "gpv.plot_topography()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'Fault_1': (vtkRenderingOpenGL2Python.vtkOpenGLActor)000001CB39AE6DC8,\n",
       " 'Fault_2': (vtkRenderingOpenGL2Python.vtkOpenGLActor)000001CB39AE6CA8,\n",
       " 'Sandstone': (vtkRenderingOpenGL2Python.vtkOpenGLActor)000001CB39AE6A68,\n",
       " 'Siltstone': (vtkRenderingOpenGL2Python.vtkOpenGLActor)000001CB39B125E8,\n",
       " 'Shale': (vtkRenderingOpenGL2Python.vtkOpenGLActor)000001CB39B12108,\n",
       " 'Sandstone_2': (vtkRenderingOpenGL2Python.vtkOpenGLActor)000001CB39B12D68,\n",
       " 'Schist': (vtkRenderingOpenGL2Python.vtkOpenGLActor)000001CB39B12E28,\n",
       " 'Gneiss': (vtkRenderingOpenGL2Python.vtkOpenGLActor)000001CB39B12768,\n",
       " 'topography': (vtkRenderingOpenGL2Python.vtkOpenGLActor)000001CB39B12888,\n",
       " 'topography_cont': (vtkRenderingOpenGL2Python.vtkOpenGLActor)000001CB3B3A3108}"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Just few surfaces\n",
    "gpv.plot_surfaces(['Siltstone', 'Gneiss'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Plotting individual surfaces"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'Fault_1': (vtkRenderingOpenGL2Python.vtkOpenGLActor)000001CB39B12F48,\n",
       " 'Fault_2': (vtkRenderingOpenGL2Python.vtkOpenGLActor)000001CB39AE6CA8,\n",
       " 'Sandstone': (vtkRenderingOpenGL2Python.vtkOpenGLActor)000001CB39AE6A68,\n",
       " 'Siltstone': (vtkRenderingOpenGL2Python.vtkOpenGLActor)000001CB39B125E8,\n",
       " 'Shale': (vtkRenderingOpenGL2Python.vtkOpenGLActor)000001CB39AE6AC8,\n",
       " 'Sandstone_2': (vtkRenderingOpenGL2Python.vtkOpenGLActor)000001CB39B12D68,\n",
       " 'Schist': (vtkRenderingOpenGL2Python.vtkOpenGLActor)000001CB39B12E28,\n",
       " 'Gneiss': (vtkRenderingOpenGL2Python.vtkOpenGLActor)000001CB39B12768,\n",
       " 'topography': (vtkRenderingOpenGL2Python.vtkOpenGLActor)000001CB39B12888,\n",
       " 'topography_cont': (vtkRenderingOpenGL2Python.vtkOpenGLActor)000001CB3B3A3108}"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gpv.plot_surfaces([\"Fault_1\"])\n",
    "gpv.plot_surfaces([\"Shale\"], clear=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Plotting input data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(vtkRenderingOpenGL2Python.vtkOpenGLActor)000001CB3B3A36A8"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gpv.plot_surface_points()\n",
    "gpv.plot_orientations()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table><tr><th>Header</th><th>Data Arrays</th></tr><tr><td>\n",
       "<table>\n",
       "<tr><th>PolyData</th><th>Information</th></tr>\n",
       "<tr><td>N Cells</td><td>22</td></tr>\n",
       "<tr><td>N Points</td><td>22</td></tr>\n",
       "<tr><td>X Bounds</td><td>2.500e+02, 1.750e+03</td></tr>\n",
       "<tr><td>Y Bounds</td><td>5.000e+02, 1.500e+03</td></tr>\n",
       "<tr><td>Z Bounds</td><td>3.000e+02, 1.500e+03</td></tr>\n",
       "<tr><td>N Arrays</td><td>1</td></tr>\n",
       "</table>\n",
       "\n",
       "</td><td>\n",
       "<table>\n",
       "<tr><th>Name</th><th>Field</th><th>Type</th><th>N Comp</th><th>Min</th><th>Max</th></tr>\n",
       "<tr><td><b>id</b></td><td>Points</td><td>int32</td><td>1</td><td>1.000e+00</td><td>8.000e+00</td></tr>\n",
       "</table>\n",
       "\n",
       "</td></tr> </table>"
      ],
      "text/plain": [
       "PolyData (0x1cb39ae6dc8)\n",
       "  N Cells:\t22\n",
       "  N Points:\t22\n",
       "  X Bounds:\t2.500e+02, 1.750e+03\n",
       "  Y Bounds:\t5.000e+02, 1.500e+03\n",
       "  Z Bounds:\t3.000e+02, 1.500e+03\n",
       "  N Arrays:\t1"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mesh = gpv.surface_points_mesh\n",
    "mesh"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "pyvista_ndarray([ 500.,  500.,  500.,  500., 1500., 1200., 1500., 1300.,\n",
       "                 1300., 1100., 1200., 1200., 1000.,  900.,  900.,  700.,\n",
       "                  700.,  700.,  500.,  300.,  500.,  500.])"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mesh.points[:, -1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mesh.n_arrays"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Plot structured grids"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[UnstructuredGrid (0x1cb3b3a3b28)\n",
       "   N Cells:\t105205\n",
       "   N Points:\t112868\n",
       "   X Bounds:\t2.000e+01, 1.980e+03\n",
       "   Y Bounds:\t2.000e+01, 1.980e+03\n",
       "   Z Bounds:\t1.600e+01, 1.584e+03\n",
       "   N Arrays:\t4,\n",
       " 'viridis']"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gpv.plot_structured_grid(\"scalar\", series = 'Strat_Series')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Interactive Block with cross sections"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "here\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<gempy.plot.vista.GemPyToVista at 0x2cc32d17908>"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gp.plot.plot_interactive_3d(geo_model, show_topography=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Interactive Plotting: Drag and drop\n",
    "\n",
    "GemPy supports interactive plotting, meaning that you can drag & drop the input data and GemPy will update the geomodel live. This does not work in the static notebook plotter, but instead you have to pass the `notebook=False` argument to open an interactive plotting window. When running the next cell you can freely move the surface points (spheres) and orientations (arrows) of the Shale horizon and see how it updates the model. \n",
    "\n",
    "**Note**: Everytime you move a data point, GemPy will recompute the geomodel. This works best whe running GemPy on a dedicated graphics card (GPU). "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'Fault_1': (vtkRenderingOpenGL2Python.vtkOpenGLActor)000001CB5D86C3A8,\n",
       " 'Fault_2': (vtkRenderingOpenGL2Python.vtkOpenGLActor)000001CB60C04E88,\n",
       " 'Sandstone': (vtkRenderingOpenGL2Python.vtkOpenGLActor)000001CB5D86C4C8,\n",
       " 'Siltstone': (vtkRenderingOpenGL2Python.vtkOpenGLActor)000001CB5D86C588,\n",
       " 'Shale': (vtkRenderingOpenGL2Python.vtkOpenGLActor)000001CB5D86C648,\n",
       " 'Sandstone_2': (vtkRenderingOpenGL2Python.vtkOpenGLActor)000001CB5D86C708,\n",
       " 'Schist': (vtkRenderingOpenGL2Python.vtkOpenGLActor)000001CB5D86C7C8,\n",
       " 'Gneiss': (vtkRenderingOpenGL2Python.vtkOpenGLActor)000001CB5D86C888}"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gpv = gp.plot_3d(geo_model, show_data=False, show_results=False, plotter_type='background')\n",
    "gpv.plot_surface_points()\n",
    "gpv.plot_orientations()\n",
    "gpv.plot_surfaces()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gpv.toggle_live_updating()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now if you move the data the model updates!\n",
    "\n",
    "To go back to static models:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "False"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gpv.toggle_live_updating()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Interactive Plotting: Programatically\n",
    "\n",
    "If the model is in live_updating model. It is also possible to change the model by passing the plotting object to the typical methods:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{0: (vtkInteractionWidgetsPython.vtkPlaneWidget)000001CB5D871408,\n",
       " 1: (vtkInteractionWidgetsPython.vtkPlaneWidget)000001CB5D871468,\n",
       " 15: (vtkInteractionWidgetsPython.vtkPlaneWidget)000001CB5D8714C8,\n",
       " 16: (vtkInteractionWidgetsPython.vtkPlaneWidget)000001CB5D871528,\n",
       " 17: (vtkInteractionWidgetsPython.vtkPlaneWidget)000001CB5D871588,\n",
       " 18: (vtkInteractionWidgetsPython.vtkPlaneWidget)000001CB5D8715E8,\n",
       " 10: (vtkInteractionWidgetsPython.vtkPlaneWidget)000001CB5D871648,\n",
       " 11: (vtkInteractionWidgetsPython.vtkPlaneWidget)000001CB5D8716A8,\n",
       " 12: (vtkInteractionWidgetsPython.vtkPlaneWidget)000001CB5D871708,\n",
       " 13: (vtkInteractionWidgetsPython.vtkPlaneWidget)000001CB5D871768,\n",
       " 14: (vtkInteractionWidgetsPython.vtkPlaneWidget)000001CB5D8717C8,\n",
       " 5: (vtkInteractionWidgetsPython.vtkPlaneWidget)000001CB5D871828,\n",
       " 6: (vtkInteractionWidgetsPython.vtkPlaneWidget)000001CB5D871888,\n",
       " 7: (vtkInteractionWidgetsPython.vtkPlaneWidget)000001CB5D8718E8,\n",
       " 8: (vtkInteractionWidgetsPython.vtkPlaneWidget)000001CB5D871948,\n",
       " 9: (vtkInteractionWidgetsPython.vtkPlaneWidget)000001CB5D8719A8,\n",
       " 2: (vtkInteractionWidgetsPython.vtkPlaneWidget)000001CB5D871A08,\n",
       " 3: (vtkInteractionWidgetsPython.vtkPlaneWidget)000001CB5D871A68,\n",
       " 4: (vtkInteractionWidgetsPython.vtkPlaneWidget)000001CB5D871AC8,\n",
       " 19: (vtkInteractionWidgetsPython.vtkPlaneWidget)000001CB5D871B28,\n",
       " 20: (vtkInteractionWidgetsPython.vtkPlaneWidget)000001CB5D871B88}"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gpv.live_updating = True\n",
    "gpv.plot_surface_points()\n",
    "gpv.plot_orientations()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>X</th>\n",
       "      <th>Y</th>\n",
       "      <th>Z</th>\n",
       "      <th>smooth</th>\n",
       "      <th>surface</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>-100.0</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>500.0</td>\n",
       "      <td>0.000002</td>\n",
       "      <td>Fault_1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>750.0</td>\n",
       "      <td>500.0</td>\n",
       "      <td>500.0</td>\n",
       "      <td>0.000002</td>\n",
       "      <td>Fault_1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1250.0</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>500.0</td>\n",
       "      <td>0.000002</td>\n",
       "      <td>Fault_2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1250.0</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>500.0</td>\n",
       "      <td>0.000002</td>\n",
       "      <td>Fault_2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>250.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>0.000002</td>\n",
       "      <td>Sandstone</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>1000.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>1200.0</td>\n",
       "      <td>0.000002</td>\n",
       "      <td>Sandstone</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>1750.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>0.000002</td>\n",
       "      <td>Sandstone</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>250.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>1300.0</td>\n",
       "      <td>0.000002</td>\n",
       "      <td>Siltstone</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>1750.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>1300.0</td>\n",
       "      <td>0.000002</td>\n",
       "      <td>Siltstone</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>1000.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>1100.0</td>\n",
       "      <td>0.000002</td>\n",
       "      <td>Siltstone</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>1750.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>1200.0</td>\n",
       "      <td>0.000002</td>\n",
       "      <td>Shale</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>250.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>1200.0</td>\n",
       "      <td>0.000002</td>\n",
       "      <td>Shale</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>1000.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>0.000002</td>\n",
       "      <td>Shale</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>250.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>900.0</td>\n",
       "      <td>0.000002</td>\n",
       "      <td>Sandstone_2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>1750.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>900.0</td>\n",
       "      <td>0.000002</td>\n",
       "      <td>Sandstone_2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>1000.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>700.0</td>\n",
       "      <td>0.000002</td>\n",
       "      <td>Sandstone_2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>250.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>700.0</td>\n",
       "      <td>0.000002</td>\n",
       "      <td>Schist</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>1750.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>700.0</td>\n",
       "      <td>0.000002</td>\n",
       "      <td>Schist</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>1000.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>500.0</td>\n",
       "      <td>0.000002</td>\n",
       "      <td>Schist</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1000.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>300.0</td>\n",
       "      <td>0.000002</td>\n",
       "      <td>Gneiss</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>250.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>500.0</td>\n",
       "      <td>0.000002</td>\n",
       "      <td>Gneiss</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>1750.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>500.0</td>\n",
       "      <td>0.000002</td>\n",
       "      <td>Gneiss</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>"
      ],
      "text/plain": [
       "         X       Y       Z    smooth      surface\n",
       "0   -100.0  1500.0   500.0  0.000002      Fault_1\n",
       "1    750.0   500.0   500.0  0.000002      Fault_1\n",
       "2   1250.0  1500.0   500.0  0.000002      Fault_2\n",
       "3   1250.0  1500.0   500.0  0.000002      Fault_2\n",
       "18   250.0  1000.0  1500.0  0.000002    Sandstone\n",
       "19  1000.0  1000.0  1200.0  0.000002    Sandstone\n",
       "20  1750.0  1000.0  1500.0  0.000002    Sandstone\n",
       "15   250.0  1000.0  1300.0  0.000002    Siltstone\n",
       "16  1750.0  1000.0  1300.0  0.000002    Siltstone\n",
       "17  1000.0  1000.0  1100.0  0.000002    Siltstone\n",
       "12  1750.0  1000.0  1200.0  0.000002        Shale\n",
       "14   250.0  1000.0  1200.0  0.000002        Shale\n",
       "21  1000.0  1000.0  1000.0  0.000002        Shale\n",
       "9    250.0  1000.0   900.0  0.000002  Sandstone_2\n",
       "10  1750.0  1000.0   900.0  0.000002  Sandstone_2\n",
       "11  1000.0  1000.0   700.0  0.000002  Sandstone_2\n",
       "6    250.0  1000.0   700.0  0.000002       Schist\n",
       "7   1750.0  1000.0   700.0  0.000002       Schist\n",
       "8   1000.0  1000.0   500.0  0.000002       Schist\n",
       "4   1000.0  1000.0   300.0  0.000002       Gneiss\n",
       "5    250.0  1000.0   500.0  0.000002       Gneiss\n",
       "13  1750.0  1000.0   500.0  0.000002       Gneiss"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "geo_model.modify_surface_points(0, X=-100, plot_object=gpv)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>X</th>\n",
       "      <th>Y</th>\n",
       "      <th>Z</th>\n",
       "      <th>smooth</th>\n",
       "      <th>surface</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>-100.0</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>500.0</td>\n",
       "      <td>0.000002</td>\n",
       "      <td>Fault_1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>750.0</td>\n",
       "      <td>500.0</td>\n",
       "      <td>500.0</td>\n",
       "      <td>0.000002</td>\n",
       "      <td>Fault_1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1250.0</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>500.0</td>\n",
       "      <td>0.000002</td>\n",
       "      <td>Fault_2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1250.0</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>500.0</td>\n",
       "      <td>0.000002</td>\n",
       "      <td>Fault_2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>250.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>0.000002</td>\n",
       "      <td>Sandstone</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>1000.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>1200.0</td>\n",
       "      <td>0.000002</td>\n",
       "      <td>Sandstone</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>1750.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>0.000002</td>\n",
       "      <td>Sandstone</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>250.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>1300.0</td>\n",
       "      <td>0.000002</td>\n",
       "      <td>Siltstone</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>1750.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>1300.0</td>\n",
       "      <td>0.000002</td>\n",
       "      <td>Siltstone</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>1000.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>1100.0</td>\n",
       "      <td>0.000002</td>\n",
       "      <td>Siltstone</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>1750.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>1200.0</td>\n",
       "      <td>0.000002</td>\n",
       "      <td>Shale</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>250.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>1200.0</td>\n",
       "      <td>0.000002</td>\n",
       "      <td>Shale</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>1000.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>0.000002</td>\n",
       "      <td>Shale</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>250.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>900.0</td>\n",
       "      <td>0.000002</td>\n",
       "      <td>Sandstone_2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>1750.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>900.0</td>\n",
       "      <td>0.000002</td>\n",
       "      <td>Sandstone_2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>1000.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>700.0</td>\n",
       "      <td>0.000002</td>\n",
       "      <td>Sandstone_2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>250.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>700.0</td>\n",
       "      <td>0.000002</td>\n",
       "      <td>Schist</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>1750.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>700.0</td>\n",
       "      <td>0.000002</td>\n",
       "      <td>Schist</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>1000.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>500.0</td>\n",
       "      <td>0.000002</td>\n",
       "      <td>Schist</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>-200.0</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>600.0</td>\n",
       "      <td>0.000001</td>\n",
       "      <td>Schist</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1000.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>300.0</td>\n",
       "      <td>0.000002</td>\n",
       "      <td>Gneiss</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>250.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>500.0</td>\n",
       "      <td>0.000002</td>\n",
       "      <td>Gneiss</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>1750.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>500.0</td>\n",
       "      <td>0.000002</td>\n",
       "      <td>Gneiss</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>"
      ],
      "text/plain": [
       "         X       Y       Z    smooth      surface\n",
       "0   -100.0  1500.0   500.0  0.000002      Fault_1\n",
       "1    750.0   500.0   500.0  0.000002      Fault_1\n",
       "2   1250.0  1500.0   500.0  0.000002      Fault_2\n",
       "3   1250.0  1500.0   500.0  0.000002      Fault_2\n",
       "18   250.0  1000.0  1500.0  0.000002    Sandstone\n",
       "19  1000.0  1000.0  1200.0  0.000002    Sandstone\n",
       "20  1750.0  1000.0  1500.0  0.000002    Sandstone\n",
       "15   250.0  1000.0  1300.0  0.000002    Siltstone\n",
       "16  1750.0  1000.0  1300.0  0.000002    Siltstone\n",
       "17  1000.0  1000.0  1100.0  0.000002    Siltstone\n",
       "12  1750.0  1000.0  1200.0  0.000002        Shale\n",
       "14   250.0  1000.0  1200.0  0.000002        Shale\n",
       "21  1000.0  1000.0  1000.0  0.000002        Shale\n",
       "9    250.0  1000.0   900.0  0.000002  Sandstone_2\n",
       "10  1750.0  1000.0   900.0  0.000002  Sandstone_2\n",
       "11  1000.0  1000.0   700.0  0.000002  Sandstone_2\n",
       "6    250.0  1000.0   700.0  0.000002       Schist\n",
       "7   1750.0  1000.0   700.0  0.000002       Schist\n",
       "8   1000.0  1000.0   500.0  0.000002       Schist\n",
       "22  -200.0  1500.0   600.0  0.000001       Schist\n",
       "4   1000.0  1000.0   300.0  0.000002       Gneiss\n",
       "5    250.0  1000.0   500.0  0.000002       Gneiss\n",
       "13  1750.0  1000.0   500.0  0.000002       Gneiss"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "geo_model.add_surface_points(-200, 1500, 600, 'Schist', plot_object=gpv)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>X</th>\n",
       "      <th>Y</th>\n",
       "      <th>Z</th>\n",
       "      <th>smooth</th>\n",
       "      <th>surface</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>-100.0</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>500.0</td>\n",
       "      <td>0.000002</td>\n",
       "      <td>Fault_1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>750.0</td>\n",
       "      <td>500.0</td>\n",
       "      <td>500.0</td>\n",
       "      <td>0.000002</td>\n",
       "      <td>Fault_1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1250.0</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>500.0</td>\n",
       "      <td>0.000002</td>\n",
       "      <td>Fault_2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1250.0</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>500.0</td>\n",
       "      <td>0.000002</td>\n",
       "      <td>Fault_2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>250.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>0.000002</td>\n",
       "      <td>Sandstone</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>1000.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>1200.0</td>\n",
       "      <td>0.000002</td>\n",
       "      <td>Sandstone</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>1750.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>0.000002</td>\n",
       "      <td>Sandstone</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>250.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>1300.0</td>\n",
       "      <td>0.000002</td>\n",
       "      <td>Siltstone</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>1750.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>1300.0</td>\n",
       "      <td>0.000002</td>\n",
       "      <td>Siltstone</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>1000.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>1100.0</td>\n",
       "      <td>0.000002</td>\n",
       "      <td>Siltstone</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>1750.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>1200.0</td>\n",
       "      <td>0.000002</td>\n",
       "      <td>Shale</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>250.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>1200.0</td>\n",
       "      <td>0.000002</td>\n",
       "      <td>Shale</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>1000.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>0.000002</td>\n",
       "      <td>Shale</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>250.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>900.0</td>\n",
       "      <td>0.000002</td>\n",
       "      <td>Sandstone_2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>1750.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>900.0</td>\n",
       "      <td>0.000002</td>\n",
       "      <td>Sandstone_2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>1000.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>700.0</td>\n",
       "      <td>0.000002</td>\n",
       "      <td>Sandstone_2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>250.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>700.0</td>\n",
       "      <td>0.000002</td>\n",
       "      <td>Schist</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>1750.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>700.0</td>\n",
       "      <td>0.000002</td>\n",
       "      <td>Schist</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>1000.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>500.0</td>\n",
       "      <td>0.000002</td>\n",
       "      <td>Schist</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1000.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>300.0</td>\n",
       "      <td>0.000002</td>\n",
       "      <td>Gneiss</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>250.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>500.0</td>\n",
       "      <td>0.000002</td>\n",
       "      <td>Gneiss</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>1750.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>500.0</td>\n",
       "      <td>0.000002</td>\n",
       "      <td>Gneiss</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>"
      ],
      "text/plain": [
       "         X       Y       Z    smooth      surface\n",
       "0   -100.0  1500.0   500.0  0.000002      Fault_1\n",
       "1    750.0   500.0   500.0  0.000002      Fault_1\n",
       "2   1250.0  1500.0   500.0  0.000002      Fault_2\n",
       "3   1250.0  1500.0   500.0  0.000002      Fault_2\n",
       "18   250.0  1000.0  1500.0  0.000002    Sandstone\n",
       "19  1000.0  1000.0  1200.0  0.000002    Sandstone\n",
       "20  1750.0  1000.0  1500.0  0.000002    Sandstone\n",
       "15   250.0  1000.0  1300.0  0.000002    Siltstone\n",
       "16  1750.0  1000.0  1300.0  0.000002    Siltstone\n",
       "17  1000.0  1000.0  1100.0  0.000002    Siltstone\n",
       "12  1750.0  1000.0  1200.0  0.000002        Shale\n",
       "14   250.0  1000.0  1200.0  0.000002        Shale\n",
       "21  1000.0  1000.0  1000.0  0.000002        Shale\n",
       "9    250.0  1000.0   900.0  0.000002  Sandstone_2\n",
       "10  1750.0  1000.0   900.0  0.000002  Sandstone_2\n",
       "11  1000.0  1000.0   700.0  0.000002  Sandstone_2\n",
       "6    250.0  1000.0   700.0  0.000002       Schist\n",
       "7   1750.0  1000.0   700.0  0.000002       Schist\n",
       "8   1000.0  1000.0   500.0  0.000002       Schist\n",
       "4   1000.0  1000.0   300.0  0.000002       Gneiss\n",
       "5    250.0  1000.0   500.0  0.000002       Gneiss\n",
       "13  1750.0  1000.0   500.0  0.000002       Gneiss"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "geo_model.delete_surface_points(22, plot_object=gpv)"
   ]
  }
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